methodology definition by authors

Definition Of Research Methodology By Authors

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Last updated on December 12th, 2024 at 07:02 am

Introduction to Research Methodology

Research methodology is a systematic process of defining, conducting, and interpreting research. It forms the backbone of any research project, guiding researchers in collecting and analyzing data. Understanding the importance of research methodology ensures a strong foundation for meaningful research outcomes.

However, over the years, the definition of research methodology by authors has been interpreted differently, and this article aims to interpret the various definitions with their intended context.

Table 1: Definitions of Research Methodology by Authors

The key elements of research methodology.

1. Philosophical Foundations

Authors such as Creswell emphasize that research methodology is rooted in philosophical assumptions. This includes perspectives like positivism interpretivism, and realism, which shape how data is collected and analyzed.

2. Research Approach

Kothari (2004) defines the approach as the overarching strategy that influences the choice of data collection methods. This includes qualitative, quantitative, and mixed methods.

3. Research Design

According to Saunders et al. (2019), the significance of research design is critical as it maps the structure and order of the entire research process, ensuring alignment with research questions.

Table 2: Types of Research Methodologies

Importance of research methodology.

Understanding research methodology is vital because it provides a structured framework, minimizing biases and ensuring valid results. As Grover and Glazier (2016) assert, the strength of research lies in the clarity of its methodology.

Steps in Research Methodology According to Various Authors

• Identifying Research Problem : Kothari stresses that this is the first crucial step, as a well-defined problem shapes the research direction.
• Literature Review : Creswell highlights that a literature review is necessary for grounding research in existing knowledge, offering context for new findings.
• Choosing a Research Method: Rajasekar emphasizes that this step involves selecting the right methodology (qualitative, quantitative, or mixed).
• Data Collection: Saunders et al. suggest that data collection methods should align with the research’s philosophical stance and objectives.
• Data Analysis: Once the data is gathered, authors like Kothari point to the importance of using appropriate statistical and interpretive methods to derive meaningful conclusions.

Practical Example: Application of Research Methodology

Imagine you are researching the impact of social media on mental health. You could choose a mixed methods approach, where quantitative data from surveys shows statistical trends, while qualitative interviews reveal deeper personal experiences.

Common Research Methodology Pitfalls to Avoid

1. Lack of Clear Objectives

Authors like Rajasekar et al. advise researchers to define clear research questions or objectives to avoid losing focus.

2. Inconsistent Data Collection Methods

According to Saunders et al., consistency in data collection methods is vital to ensure valid and comparable results.

3. Biased Analysis

Kothari warns that analysis should be unbiased and follow a logical approach to avoid skewed results.

Table 3: Challenges in Research Methodology

What is the role of research methodology in a study.

Research methodology provides a structured framework for designing, conducting, and analyzing research. It ensures that the research process is systematic and reliable.

How do qualitative and quantitative methodologies differ?

Qualitative methodology focuses on descriptive, non-numerical data, while quantitative methodology is data-driven and relies on statistical analysis.

Why is it important to align research methodology with philosophical assumptions?

Aligning methodology with philosophical assumptions ensures consistency in the approach, influencing how data is interpreted and validated.

In conclusion, the definitions of research methodology offered by various authors highlight its integral role in academic research. Research methodology is the backbone of any study, serving as the strategic framework that ensures accuracy, validity, and reliability of results.

While different scholars may emphasize unique aspects of methodology, they all converge on the understanding that it is a systematic and well-structured approach essential for solving research problems.

Whether one adopts qualitative, quantitative, or mixed methods, the chosen methodology dictates how data is gathered, analyzed, and interpreted, ultimately shaping the overall impact and credibility of the research.

As research continues to evolve, methodologies are refined, proving that a well-considered approach is crucial to producing meaningful and reproducible results.

My journey in academia began as a dedicated researcher, specializing in the fascinating world of biochemistry. Over the years, I’ve had the privilege of mentoring Master’s and PhD students, collaborating on research papers that pushed the boundaries of knowledge. Now, post-retirement, I’ve embarked on a new chapter, sharing my academic expertise through freelance work on platforms like YouTube and Upwork. Here, I investigate the finer points of scholarly research, guiding aspiring writers through the intricacies of formatting, composing compelling narratives, and navigating the publication process.

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What Is Research Methodology?

I f you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

• What exactly research methodology means
• What qualitative , quantitative and mixed methods are
• What sampling strategy is
• What data collection methods are
• What data analysis methods are
• How to choose your research methodology
• Example of a research methodology

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What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

• What type of data to collect (e.g., qualitative or quantitative data )
• Who  to collect it from (i.e., the sampling strategy )
• How to  collect  it (i.e., the data collection method )
• How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

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What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

• Interviews (which can be unstructured, semi-structured or structured)
• Focus groups and group interviews
• Surveys (online or physical surveys)
• Observations (watching and recording activities)
• Biophysical measurements (e.g., blood pressure, heart rate, etc.)
• Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Interpretative phenomenological analysis (IPA)
• Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

• Descriptive statistics (e.g. means, medians, modes )
• Inferential statistics (e.g. correlation, regression, structural equation modelling)

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

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MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

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What is Research Methodology? Definition, Types, and Examples

Table of Contents

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

Types of research methodology

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Nonprobability sampling

This involves feedback based on a researcher’s sample selection capabilities and not on a fixed selection process. The different types of nonprobability sampling methods are:

• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

What are data analysis methods?

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

How to write a research methodology ?

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

• Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
• Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
• The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
• Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
• What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
• What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
• Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Methodology

Research can be defined as “an activity that involves finding out, in a more or less systematic way, things you did not know” (Walliman and Walliman, 2011, p.7).

“Methodology is the philosophical framework within which the research is conducted or the foundation upon which the research is based” (Brown, 2006).

Research Methodology chapter of a research describes research methods, approaches and designs in detail highlighting those used throughout the study, justifying my choice through describing advantages and disadvantages of each approach and design taking into account their practical applicability to our research.

O’Leary (2004, p.85) describes methodology as the framework which is associated with a particular set of paradigmatic assumptions that we will use to conduct our research. Allan and Randy (2005) insist that when conducting a research methodology should meet the following two criteria:

Firstly, the methodology should be the most appropriate to achieve objectives of the research.

Secondly, it should be made possible to replicate the methodology used in other researches of the same nature

The differences between objectivist and subjectivist dimensions are presented by Cohen et al (2007) as taken from Greenfield (1975) in the following manner:

The most comprehensive information regarding vital aspects of methodology is provided by Jackson (2011) that can be summarised in the following table:

Source: (Jackson, 2011)

Allan, AJ, Randy, LJ, 2005, Writing the Winning Thesis or Dissertation. A Step-by-Step Guide, Corwin Press, California Brown RB, 2006, Doing Your Dissertation in Business and Management: The Reality of Research and Writing, Sage Publications Cohen, L, Manion, L, Morrison, K & Morrison, RB, 2007, Research Methods in Education, Routledge O’Leary Z. 2004 “ The essential guide to doing research”. Sage.

Walliman, N. S. & Walliman N. (2011) “Research methods: the basics” Taylor and Francis

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Research Methodology – Types, Examples and writing Guide

Table of Contents

Research methodology is the backbone of any scientific or academic study, outlining the specific strategies and tools used to collect, analyze, and interpret data. A well-defined research methodology ensures that a study is conducted systematically, yielding reliable and valid results. This article explores the concept of research methodology, its various types, practical examples, and a step-by-step guide to writing a methodology section.

Research Methodology

Research methodology refers to the systematic plan and approach employed in a study to answer research questions or test hypotheses. It defines the tools, techniques, and procedures used to collect and analyze data, ensuring the research is structured and replicable.

For example, a study exploring the impact of remote learning on student performance might use surveys to collect data and statistical analysis to evaluate the findings.

Importance of Research Methodology

• Clarity and Focus: Provides a clear roadmap for the study, ensuring alignment with research objectives.
• Reliability: Ensures the study’s results can be replicated and trusted.
• Validity: Confirms that the methods used are appropriate for answering the research questions.
• Transparency: Allows others to evaluate the study’s credibility and rigor.
• Adaptability: Enables adjustments to the research process if unforeseen challenges arise.

Research Methodology Structure

1. introduction.

The introduction provides an overview of the research methodology, explaining its purpose and relevance to the study. It briefly outlines the chosen approach (qualitative, quantitative, or mixed methods) and justifies its suitability for addressing the research questions or hypotheses.

• Example: “This research employs a mixed-methods approach to explore the impact of remote work on employee productivity, combining quantitative surveys and qualitative interviews to gain a comprehensive understanding of the phenomenon.”

2. Research Design

This section describes the overall framework or design of the study. Common research designs include experimental, descriptive, correlational, or exploratory. The design should align with the research objectives and questions.

• Type of design (e.g., experimental, case study, longitudinal).
• Justification for the selected design.
• Example: “A descriptive research design was chosen to investigate patterns of online shopping behavior among millennials during the pandemic.”

3. Data Collection Methods

Detail the methods and tools used to gather data. This includes the type of data (primary or secondary) and the specific techniques employed.

• Data sources (e.g., surveys, interviews, observations, archival records).
• Instruments or tools used (e.g., questionnaires, scales, software).
• Procedures for data collection.
• Example: “Primary data was collected through structured questionnaires distributed online, while secondary data was sourced from industry reports and previous research studies.”

4. Sampling

Explain the sampling method used to select participants or data points for the study. Include the sample size, criteria for inclusion or exclusion, and sampling technique.

• Sampling population.
• Sampling technique (e.g., random, stratified, purposive).
• Rationale for the chosen sample size.
• Example: “A stratified random sampling method was employed to ensure representation across age groups. The final sample comprised 200 participants aged 18–60.”

5. Data Analysis Techniques

Describe the techniques or tools used to analyze the collected data. This section should differentiate between qualitative and quantitative data analysis methods.

• Quantitative analysis: statistical tools (e.g., SPSS, regression analysis).
• Qualitative analysis: thematic analysis, coding, or content analysis.
• Software or tools used (e.g., NVivo, Excel, Python).
• Example: “Quantitative data was analyzed using SPSS software for descriptive and inferential statistics, while qualitative data was thematically coded using NVivo to identify recurring patterns.”

6. Ethical Considerations

Discuss the ethical measures taken to ensure participant safety and data integrity. Ethical considerations reflect the study’s adherence to moral and professional standards.

• Informed consent from participants.
• Confidentiality and data security.
• Approval from an institutional review board (IRB).
• Example: “All participants provided informed consent, and their anonymity was ensured by assigning unique identification codes. The study was approved by the Institutional Review Board (IRB) at XYZ University.”

7. Limitations of the Methodology

Acknowledge any methodological limitations that may affect the validity or reliability of the results.

• Constraints such as sample size, geographic scope, or time frame.
• Potential biases or challenges.
• Example: “The study’s primary limitation was the reliance on self-reported data, which may be subject to response bias.”

8. Justification of Methodology

Provide a rationale for choosing specific methods and tools over alternatives. This reinforces the credibility of the methodology and its alignment with research objectives.

• Explanation of why chosen methods are appropriate.
• Comparison with other possible methods.
• Example: “The mixed-methods approach was selected to capture both numerical trends and in-depth personal experiences, ensuring a holistic understanding of the research problem.”

9. Operational Definitions (Optional)

Define key terms or concepts used in the study to ensure clarity and consistency.

Example: “For this study, ‘remote work productivity’ refers to the number of tasks completed within standard working hours, as self-reported by participants.”

Types of Research Methodology

1. qualitative research methodology.

Qualitative methodology focuses on understanding human experiences, behaviors, and social phenomena. It uses non-numerical data and is often exploratory.

• Subjective and descriptive.
• Data collected through interviews, focus groups, or observations.
• Analyzes themes, patterns, and narratives.
• Example: A study exploring teachers’ perceptions of remote learning challenges during the COVID-19 pandemic.

2. Quantitative Research Methodology

Quantitative methodology focuses on measuring and analyzing numerical data to test hypotheses or answer research questions. It is often used for studies requiring statistical analysis.

• Objective and structured.
• Data collected through surveys, experiments, or secondary datasets.
• Statistical methods used for data analysis.
• Example: Examining the relationship between study hours and academic performance among high school students.

3. Mixed Methods Research Methodology

Mixed methods combine qualitative and quantitative approaches to provide a comprehensive understanding of a research problem.

• Integrates numerical data with detailed narratives.
• Offers both breadth and depth in analysis.
• Often uses sequential or concurrent designs.
• Example: Investigating how healthcare workers perceive telemedicine (qualitative) and evaluating patient satisfaction scores (quantitative).

4. Descriptive Research Methodology

Descriptive research aims to describe characteristics, phenomena, or trends in a specific population or setting.

• Non-experimental.
• Data collected through surveys, case studies, or observations.
• Focuses on “what” rather than “why” or “how.”
• Example: Surveying college students to understand their preferred learning platforms.

5. Experimental Research Methodology

Experimental research investigates cause-and-effect relationships by manipulating variables and observing outcomes.

• Involves control and experimental groups.
• Uses randomization to reduce bias.
• Common in natural and social sciences.
• Example: Testing the effectiveness of a new drug on reducing symptoms compared to a placebo.

6. Correlational Research Methodology

Correlational research examines the relationship between two or more variables without manipulating them.

• Identifies positive, negative, or no correlation.
• Cannot establish causation.
• Data often collected through surveys or secondary datasets.
• Example: Analyzing the correlation between screen time and sleep quality among teenagers.

Examples of Research Methodology

1. education.

• Topic: The effectiveness of project-based learning on student engagement.
• Methodology: Mixed methods involving student surveys (quantitative) and teacher interviews (qualitative).

2. Healthcare

• Topic: The impact of physical activity on managing type 2 diabetes.
• Methodology: Quantitative approach using clinical trials to measure blood glucose levels.

3. Business

• Topic: Factors influencing employee job satisfaction in remote work environments.
• Methodology: Descriptive research using online surveys to collect data from employees across industries.

4. Environmental Studies

• Topic: The effect of urbanization on local biodiversity.
• Methodology: Descriptive research involving field observations and quantitative data analysis of species populations.

How to Write the Methodology Section

Step 1: provide an overview.

Begin by explaining the overall research approach (qualitative, quantitative, or mixed methods) and justifying its suitability for addressing the research questions.

• Example: “This study employs a mixed-methods approach to explore the impact of remote work on employee productivity. The combination of quantitative surveys and qualitative interviews provides a comprehensive understanding of the phenomenon.”

Step 2: Describe the Research Design

Outline the specific design used, such as experimental, descriptive, or correlational, and explain why it was chosen.

• Example: “A correlational design was selected to analyze the relationship between screen time and sleep quality among high school students.”

Step 3: Detail the Data Collection Methods

Explain how data was collected, including tools, instruments, and procedures.

• Example: “Data was collected using an online survey distributed to 500 participants. The survey included closed-ended questions measuring job satisfaction and open-ended questions capturing employee experiences.”

Step 4: Specify the Sampling Method

Describe the sampling strategy, including sample size, selection criteria, and sampling technique (e.g., random, stratified, convenience).

• Example: “A stratified sampling technique was employed to ensure representation across different age groups. The final sample included 200 respondents aged 18–60.”

Step 5: Describe Data Analysis Techniques

Explain the methods used to analyze the data, whether statistical or thematic.

• Example: “Quantitative data was analyzed using SPSS software, employing descriptive statistics and regression analysis. Qualitative data from interviews was thematically coded to identify patterns and themes.”

Step 6: Address Ethical Considerations

Discuss ethical measures such as informed consent, confidentiality, and data security.

• Example: “All participants provided informed consent, and data was anonymized to maintain confidentiality. Ethical approval was obtained from the institutional review board.”

Step 7: Justify Your Choices

Provide a rationale for selecting the chosen methods and explain their relevance to the research objectives.

• Example: “The use of surveys allowed for efficient data collection from a large sample, while interviews provided in-depth insights into individual experiences.”

Tips for Writing a Strong Methodology Section

• Be Detailed and Specific: Provide enough detail to allow replication of your study.
• Maintain Objectivity: Use neutral language and avoid subjective statements.
• Link to Objectives: Ensure all methods align with the study’s research questions or hypotheses.
• Use Subheadings: Organize the section into clear subsections for readability.
• Cite Sources: Reference any tools, instruments, or previous studies that informed your methodology.

Common Mistakes to Avoid

• Lack of Clarity: Ambiguous descriptions can confuse readers and undermine credibility.
• Insufficient Detail: Omitting key steps or procedures can make the study irreproducible.
• Ignoring Limitations: Failing to acknowledge methodological limitations reduces transparency.
• Misalignment with Objectives: Methods that do not address the research questions weaken the study’s validity.

The research methodology is a vital component of any study, laying the foundation for credible and reliable results. By selecting the appropriate type—whether qualitative, quantitative, or mixed methods—and providing a clear, detailed explanation of the processes involved, researchers can ensure that their work is both rigorous and replicable. Following the writing guide and addressing common mistakes will help create a robust methodology section, contributing to the overall strength and impact of the research.

• Creswell, J. W. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . Sage Publications.
• Babbie, E. (2020). The Practice of Social Research . Cengage Learning.
• Bryman, A. (2016). Social Research Methods . Oxford University Press.
• Patton, M. Q. (2015). Qualitative Research & Evaluation Methods: Integrating Theory and Practice . Sage Publications.
• Flick, U. (2018). An Introduction to Qualitative Research . Sage Publications.

About the author

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Research Methodologies

• What are research designs?

What are research methodologies?

Quantitative research methodologies, qualitative research methodologies, mixed method methodologies, selecting a methodology.

• What are research methods?
• Additional Sources

According to Dawson (2019),a research methodology is the primary principle that will guide your research.  It becomes the general approach in conducting research on your topic and determines what research method you will use. A research methodology is different from a research method because research methods are the tools you use to gather your data (Dawson, 2019).  You must consider several issues when it comes to selecting the most appropriate methodology for your topic.  Issues might include research limitations and ethical dilemmas that might impact the quality of your research.  Descriptions of each type of methodology are included below.

Quantitative research methodologies are meant to create numeric statistics by using survey research to gather data (Dawson, 2019).  This approach tends to reach a larger amount of people in a shorter amount of time.  According to Labaree (2020), there are three parts that make up a quantitative research methodology:

• Sample population
• How you will collect your data (this is the research method)
• How you will analyze your data

Once you decide on a methodology, you can consider the method to which you will apply your methodology.

Qualitative research methodologies examine the behaviors, opinions, and experiences of individuals through methods of examination (Dawson, 2019).  This type of approach typically requires less participants, but more time with each participant.  It gives research subjects the opportunity to provide their own opinion on a certain topic.

Examples of Qualitative Research Methodologies

• Action research:  This is when the researcher works with a group of people to improve something in a certain environment.  It is a common approach for research in organizational management, community development, education, and agriculture (Dawson, 2019).
• Ethnography:  The process of organizing and describing cultural behaviors (Dawson, 2019).  Researchers may immerse themselves into another culture to receive in "inside look" into the group they are studying.  It is often a time consuming process because the researcher will do this for a long period of time.  This can also be called "participant observation" (Dawson, 2019).
• Feminist research:  The goal of this methodology is to study topics that have been dominated by male test subjects.  It aims to study females and compare the results to previous studies that used male participants (Dawson, 2019).
• Grounded theory:  The process of developing a theory to describe a phenomenon strictly through the data results collected in a study.  It is different from other research methodologies where the researcher attempts to prove a hypothesis that they create before collecting data.  Popular research methods for this approach include focus groups and interviews (Dawson, 2019).

A mixed methodology allows you to implement the strengths of both qualitative and quantitative research methods.  In some cases, you may find that your research project would benefit from this.  This approach is beneficial because it allows each methodology to counteract the weaknesses of the other (Dawson, 2019).  You should consider this option carefully, as it can make your research complicated if not planned correctly.

What should you do to decide on a research methodology?  The most logical way to determine your methodology is to decide whether you plan on conducting qualitative or qualitative research.  You also have the option to implement a mixed methods approach.  Looking back on Dawson's (2019) five "W's" on the previous page , may help you with this process.  You should also look for key words that indicate a specific type of research methodology in your hypothesis or proposal.  Some words may lean more towards one methodology over another.

Quantitative Research Key Words

• How satisfied

Qualitative Research Key Words

• Experiences
• Thoughts/Think
• Relationship
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Methodology for research I

Rakesh garg.

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Address for correspondence: Dr. Rakesh Garg, Room No. 139, First Floor, Department of Anaesthesiology, Pain and Palliative Care, Dr. BRAIRCH, All India Institute of Medical Sciences, Ansari Nagar, New Delhi - 110 029, India. E-mail: [email protected]

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

The conduct of research requires a systematic approach involving diligent planning and its execution as planned. It comprises various essential predefined components such as aims, population, conduct/technique, outcome and statistical considerations. These need to be objective, reliable and in a repeatable format. Hence, the understanding of the basic aspects of methodology is essential for any researcher. This is a narrative review and focuses on various aspects of the methodology for conduct of a clinical research. The relevant keywords were used for literature search from various databases and from bibliographies of the articles.

Key words: Bias, blinding, confounders, population, randomisation, research, sample size, study design, study tools

INTRODUCTION

Research is a process for acquiring new knowledge in systematic approach involving diligent planning and interventions for discovery or interpretation of the new-gained information.[ 1 , 2 ] The outcome reliability and validity of a study would depend on well-designed study with objective, reliable, repeatable methodology with appropriate conduct, data collection and its analysis with logical interpretation. Inappropriate or faulty methodology would make study unacceptable and may even provide clinicians faulty information. Hence, the understanding the basic aspects of methodology is essential.

This is a narrative review based on existing literature search. This review focuses on specific aspects of the methodology for conduct of a research/clinical trial. The relevant keywords for literature search included ‘research’, ‘study design’, ‘study controls’, ‘study population’, ‘inclusion/exclusion criteria’, ‘variables’, ‘sampling’, ‘randomisation’, ‘blinding’, ‘masking’, ‘allocation concealment’, ‘sample size’, ‘bias’, ‘confounders’ alone and in combinations. The search engine included PubMed/MEDLINE, Google Scholar and Cochrane. The bibliographies of the searched articles were specifically searched for missing manuscripts from the search engines and manually from the print journals in the library.

The following text highlights/describes the basic essentials of methodology which needs to be adopted for conducting a good research.

Aims and objectives of study

The aims and objectives of research need to be known thoroughly and should be specified before start of the study based on thorough literature search and inputs from professional experience. Aims and objectives state whether nature of the problem (formulated as research question or research problem) has to be investigated or its solution has to be found by different more appropriate method. The lacunae in existing knowledge would help formulate a research question. These statements have to be objective specific with all required details such as population, intervention, control, outcome variables along with time interventions.[ 3 , 4 , 5 ] This would help formulate a hypothesis which is a scientifically derived statement about a particular problem in the defined population. The hypothesis generation depends on the type of study as well. Researcher observation related to any aspect initiates hypothesis generation. A cross-sectional survey would generate hypothesis. An observational study establishes associations and supports/rejects the hypothesis. An experiment would finally test the hypothesis.[ 5 , 6 , 7 ]

STUDY POPULATION AND PATIENT SELECTION, STUDY AREA, STUDY PERIOD

The flow of study in an experimental design has various sequential steps [ Figure 1 ].[ 1 , 2 , 6 ] Population refers to an aggregate of individuals, things, cases, etc., i.e., observation units that are of interest and remain the focus of investigation. This reference population or target population is the group on which the study outcome would be extrapolated.[ 6 ] Once this target population is identified, researcher needs to assess whether it is possible to study all the individuals for an outcome. Usually, all cannot be included, so a study population is sampled. The important attribute of a sample is that every individual should have equal and non-zero chance of getting included in the study. The sample should be made independently, i.e., selection of one does not influence inclusion or exclusion of other. In clinical practice, the sampling is restricted to a particular place (patients attending to clinics or posted for surgery) or includes multiple centres rather than sampling the universe. Hence, the researcher should be cautious in generalising the outcomes. For example, in a tertiary care hospital, patients are referred and may have more risk factors as compared to primary centres where a patient with lesser severity are managed. Hence, researchers must disclose details of the study area. The study period needs to be disclosed as it would make readers understand the population characteristics. Furthermore, study period would tell about relevance of the study with respect to the present period.

Flow of an experimental study

The size of sample has to be pre-determined, analytically approached and sufficiently large to represent the population.[ 7 , 8 , 9 ] Including a larger sample would lead to wastage of resources, risk that the true treatment effect may be missed due to heterogeneity of large population and would be time-consuming.[ 6 ] If a study is too small, it will not provide the suitable answer to research question. The main determinant of the sample size includes clinical hypothesis, primary endpoint, study design, probability of Type I and II error, power, minimum treatment difference of clinical importance.[ 7 ] Attrition of patients should be attended during the sample size calculation.[ 6 , 9 ]

SELECTION OF STUDY DESIGN

The appropriate study design is essential for the intervention outcome in terms of its best possible and most reliable estimate. The study design selection is based on parameters such as objectives, therapeutic area, treatment comparison, outcome and phase of the trial.[ 6 ] The study design may be broadly classified as:[ 5 , 6 , 7 ]

Quantitative:

• Descriptive: Case report, case series, survey
• Analytical: Case-control, cohort, cross-sectional
• Experimental: Randomised controlled trial (RCT), quasi-experiment

Qualitative.

For studying causality, analytical observational studies would be prudent to avoid posing risk to subjects. For clinical drugs or techniques, experimental study would be more appropriate.[ 6 ] The treatments remain concurrent, i.e. the active and control interventions happen at the same period in RCT. It may parallel group design wherein treatment and control groups are allocated to different individuals. This requires comparing a placebo group or a gold standard intervention (control) with newer agent or technique.[ 6 ] In matched-design RCT, randomisation is between matched pairs. For cross-over study design, two or more treatments are administered sequentially to the same subject and thus each subject acts as its own control. However, researches should be aware of ‘carryover effect’ of the previous intervention and suitable wash period needs to be ensured. In cohort study design, subjects with disease/symptom or free of study variable are followed for a particular period. The cross-sectional study examines the prevalence of the disease, surveys, validating instruments, tools and questionnaires. The qualitative research is a study design wherein health-related issue in the population is explored with regard to its description, exploration and explanation.[ 6 ]

Selection of controls

The control is required because disease may be self-remitting, Hawthorne effect (change in response or behaviours of subjects when included in study), placebo effect (patients feel improvement even with placebo), effect of confounder, co-intervention and regression to the mean phenomenon (for example, white coat hypertension, i.e. patients at recruitment may have higher study parameter but subsequently may get normal).[ 2 , 6 , 7 ] The control could be a placebo, no treatment, different dose or regimen or intervention or the standard/gold treatment. Avoiding a routine care for placebo is not desirable and unethical. For instance, for studying analgesic regimen, it would be unethical not to administer analgesics in a control group. It is advisable to continue standard of care, i.e. providing routine analgesics even in control group. The use of placebo or no treatment may be considered where no current proven intervention exists or placebo is required to evaluate efficacy or safety of an intervention without serious or irreversible harm.

The comparisons to be made in the study among groups also need to be specified.[ 6 , 7 , 9 ] These comparisons may prove superiority, non-inferiority or equivalence among groups. The superiority trials demonstrate superiority either to a placebo in a placebo-controlled trial or to an active control treatment. The non-inferiority trials would prove that the efficacy of an intervention is no worse than that of the active comparative treatment. The equivalence trials demonstrate that the outcome of two or more interventions differs by a clinically unimportant margin and either technique or drug may be clinically acceptable.

STUDY TOOLS

The study tools such as measurements scales, questionnaires and scoring systems need to be specified with an objective definition. These tools should be validated before its use and appropriate use by the research staff is mandatory to avoid any bias. These tools should be simple and easily understandable to everyone involved in the study.

Inclusion/exclusion criteria

In clinical research, specific group of relatively homogeneous patient population needs to be selected.[ 6 ] Inclusion and exclusion criteria define who can be included or excluded from the study sample. The inclusion criteria identify the study population in a consistent, reliable, uniform and objective manner. The exclusion criteria include factors or characteristics that make the recruited population ineligible for the study. These factors may be confounders for the outcome parameter. For example, patients with liver disease would be excluded if coagulation parameters would impact the outcome. The exclusion criteria are inclusive of inclusion criteria.

VARIABLES: PRIMARY AND SECONDARY

Variables are definite characteristics/parameters that are being studied. Clear, precise and objective definition for measurement of these characteristics needs to be defined.[ 2 ] These should be measurable and interpretable, sensitive to the objective of the study and clinically relevant. The most common end-point is related to efficacy, safety and quality of life. The study variables could be primary or secondary.[ 6 ] The primary end-point, usually one, provides the most relevant, reliable and convincing evidence related to the aim and objective. It is the characteristic on the basis of which research question/hypothesis has been formulated. It reflects clinically relevant and important treatment benefits. It determines the sample size. Secondary end-points are the other objectives indirectly related to primary objective with regard to its close association or they may be some associated effects/adverse effects related to intervention. The measurement timing of the variables must be defined a priori . These are usually done at screening, baseline and completion of trial.

The study end-point parameter may be clinical or surrogate in nature. A clinical end-point is related directly to clinical implications with regard to beneficial outcome of the intervention. The surrogate end-point is indirectly related to patient clinical benefit and is usually measures laboratory measurement or physical sign as a substitute for a clinically meaningful end-point. Surrogate end-points are more convenient, easily measurable, repeatable and faster.

SAMPLING TECHNIQUES: RANDOMISATION, BLINDING/MASKING AND ALLOCATION CONCEALMENT

Randomisation.

Randomisation or random allocation is a method to allocate individuals into one of the groups (arms) of a study.[ 1 , 2 ] It is the basic assumption required for statistical analysis of data. The randomisation would maximise statistical power, especially in subgroup analyses, minimise selection bias and minimise allocation bias (or confounding). This leads to distribution of all the characteristics, measured or non-measured, visible or invisible and known or unknown equally into the groups. Randomisation uses various strategies as per the study design and outcome.

Probability sampling/randomisation

Simple/unrestricted: Each individual of the population has the same chance of being included in the sample. This is used when population is small, homogenous and the sampling frame is available. For example, lottery method, table of random numbers or computer-generated

Stratified: It is used in non-homogenous population. Population is divided into homogenous groups (strata), and the sample is drawn for each stratum at random. It keeps the ‘characteristics’ of the participants (for example, age, weight or physical status) as similar as possible across the study groups. The allocation to strata can be by equal or proportional allocation

Systematic: This is used when complete and up-to-date sampling frame is available. The first unit is selected at random and the rest get selected automatically according to some pre-designed pattern

Cluster: This applies for large geographical area. Population is divided into a finite numbers of distinct and identifiable units (sampling units/element). A group of such elements is a cluster and sampling of these clusters is done. All units of the selected clusters are included in the study

Multistage: This applies for large nationwide surveys. Sampling is done in stages using random sampling. Here, sub-sampling within the selected clusters is done. If procedure is repeated in more number of stages, then they termed as multistage sampling

Multiphase: Here, some data are collected from whole of the units of a sample, and other data are collected from a sub-sample of the units constituting the original sample (two-phase sampling). If three or more phases are used, then they termed as multiphase sampling.

Non-probability sampling/randomisation

This technique does not give equal and non-zero chances to all the individuals in the population to be selected in the sample.

Convenience: Sampling is done as per the convenience of the investigator, i.e., easily available

Purposive/judgemental/selective/subjective: The sample is selected as per judgement of investigator

Quota: It is done as per judgement of the interviewer based on some specified characteristics such as sex and physical status.

ALLOCATION CONCEALMENT

Allocation concealment refers to the process ensuring the person who generates the random assignment remains blind to what arm the person will be allotted.[ 8 , 9 , 10 ] It is a strategy to avoid ascertainment or selection bias. For example, based on an outcome, researcher may recruit a specific category as lesser sicker patients to a particular group and vice versa to the other group. This selective recruitment would underestimate (if treatment group is sicker) or overestimate (if control group is sicker) the intervention effect.[ 9 ] The allocation should be concealed from investigator till the initiation of intervention. Hence, randomisation should be performed by an independent person who is not involved in the conduct of the study or its monitoring. The randomisation list is kept secret. The methods of allocation concealment include:[ 9 , 10 ]

Central randomisation: Some centrally independent authority performs randomisation and informs the investigators via telephone, E-mail or fax

Pharmacy controlled: Here, pharmacy provides coded drugs for use

Sequentially numbered containers: Identical containers equal in weight, similar in appearance and tamper-proof are used

Sequentially numbered, opaque, sealed envelopes: The randomised numbers are concealed in opaque envelope to be opened just before intervention and are the most common and easy to perform method.

BLINDING/MASKING

Blinding ensures the group to which the study subjects are assigned not known or easily ascertained by those who are ‘masked’, i.e., participants, investigators, evaluators or statistician to limit occurrence of bias.[ 1 , 2 ] It confirms that the intervention and standard or placebo treatment appears the same. Blinding is different from allocation concealment. Allocation concealment is done before, whereas blinding is done at and after initiation of treatment. In situations such as study drugs with different formulations or medical versus surgical interventions, blinding may not be feasible.[ 8 ] Sham blocks or needling in subjects may not be ethical. In such situation, the outcome measurement should be made objective to the fullest to avoid bias and whosoever may be masked should be blinded. The research manuscript must mention the details about blinding including who was blinded after assignment to interventions and process or technique used. Blinding could be:[ 8 , 9 ]

Unblinded: The process cannot conceal randomisation

Single blind: One of the participants, investigators or evaluators remains masked

Double-blind: The investigator and participants remained masked

Triple blind: Not only investigator but also participant maintains a blind data analysis.

BIAS AND CONFOUNDERS

Bias is a systematic deviation of the real, true effect (better or worst outcome) resulting from faulty study design.[ 1 , 2 ] The various steps of study such as randomisation, concealment, blinding, objective measurement and strict protocol adherence would reduce bias.

The various possible and potential biases in a trial can be:[ 7 ]

Investigator bias: An investigator either consciously or subconsciously favours one group than other

Evaluator bias: The investigator taking end-point variable measurement intentionally or unintentionally favours one group over other. It is more common with subjective or quality of life end-points

Performance bias: It occurs when participant knows of exposure to intervention or its response, be it inactive or active

Selection bias: This occurs due to sampling method such as admission bias (selective factors for admission), non-response bias (refusals to participate and the population who refused may be different from who participated) or sample is not representative of the population

Ascertainment or information bias: It occurs due to measurement error or misclassification of patient. For example, diagnostic bias (more diagnostic procedures performed in cases as compared with controls), recall bias (error of categorisation, investigator aggressively search for exposure variables in cases)

Allocation bias: Allocation bias occurs when the measured treatment effect differs from the true treatment effect

Detection bias: It occurs when observations in one group are not as vigilantly sought as in the other

Attrition bias/loss-to-follow-up bias: It occurs when patient is lost to follow-up preferentially in a particular group.

Confounding occurs when outcome parameters are affected by effects of other factors not directly relevant to the research question.[ 1 , 7 ] For example, if impact of drug on haemodynamics is studied on hypertensive patients, then diabetes mellitus would be confounder as it also effects the hemodynamic response to autonomic disturbances. Hence, it becomes prudent during the designing stage for a study that all potential confounders should be carefully considered. If the confounders are known, then they can be adjusted statistically but with loss of precision (statistical power). Hence, confounding can be controlled either by preventing it or by adjusting for it in the statistical analysis. The confounding can be controlled by restriction by study design (for example, restricted age range as 2-6 years), matching (use of constraints in the selection of the comparison group so that the study and comparison group have similar distribution with regard to potential confounder), stratification in the analysis without matching (involves restriction of the analysis to narrow ranges of the extraneous variable) and mathematical modelling in the analysis (use of advanced statistical methods of analysis such as multiple linear regression and logistic regression). Strategies during data analysis include stratified analysis using the Mantel-Haenszel method to adjust for confounders, using a matched design approach, data restriction and model fitting using regression techniques.

Basic understanding of the methodology is essential to have reliable, repeatable and clinically acceptable outcome. The study plan including all its components needs to be designed before start of the study, and the study protocol should be strictly adhered during the conduct of study.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

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What is Research Methodology? Definition, Types, and Examples

Introduction to Research Methodology

Research methodology may seem like a purely academic term, but it's the foundation of any successful investigation, regardless of the subject – from ancient history to consumer behavior or the efficacy of new medications. Think of it as the architect's blueprint for a building: without a well-defined research methodology, your project is at risk of collapsing due to faulty data and biased conclusions.

What exactly is research methodology? It's simply the framework that guides your research. It's the roadmap that helps you manage the complexities of data collection, analysis, and interpretation. A robust methodology ensures your study is trustworthy, repeatable, and ultimately, makes a valuable contribution to your field.

Why Research Methodology Matters

Choosing the right research methodology is akin to selecting the right tool for a job. Using a hammer to drive a screw isn’t effective. Similarly, different research questions demand different approaches. If you're measuring something quantifiable, like the average income of a specific group, a quantitative methodology, emphasizing numerical data and statistical analysis, is ideal.

If you're exploring complex social phenomena, like the experiences of refugees, a qualitative methodology, focused on in-depth interviews and observations, is more suitable. Sometimes, a mixed methods approach, integrating both quantitative and qualitative techniques, offers the most complete understanding. For instance, a study on a new educational program might use quantitative data (test scores) to measure its efficacy and qualitative data (interviews) to understand how and why it works.

Key Components of Research Methodology

A strong research methodology typically includes these components:

• Research Question: What are you trying to uncover? A clear, focused question is the bedrock of any study.
• Research Design: This is your overarching strategy for answering your research question. It outlines the study type (e.g., experiment, survey, case study) and data collection and analysis methods.
• Data Collection Methods: How will you gather information? Options include surveys, interviews, experiments, observations, or document analysis. Consider historical research: analyzing primary sources like letters and diaries is a core data collection method.
• Data Analysis Techniques: How will you interpret the collected data? This might involve statistical analysis for quantitative data or thematic analysis for qualitative data.
• Ethical Considerations: Ethical conduct is crucial, ensuring respect for participants' rights and well-being. Historical research, for example, must carefully consider source interpretation to prevent misrepresentation.

By carefully considering each component, you can create a research methodology suited to your specific question, producing dependable and meaningful results. As we've seen, choosing the right methodology isn't about rigid rules, but about informed decisions that lead to deeper understanding.

Quantitative Research Methods

Let's explore quantitative research methods in more detail. Quantitative research works with numbers, concrete data, and statistical analysis. It’s the best approach when you need to measure or quantify a phenomenon. For instance, to determine the effectiveness of a new teaching method, you might compare test scores of students taught with the new method versus a traditional one.

When to Use Quantitative Research Methods

Quantitative methods are particularly useful when you want to:

• Measure Prevalence: How many people share a certain belief? What percentage of a population uses a specific product?
• Establish Relationships: Does a connection exist between education level and income? Does smoking correlate with lung cancer risk?
• Test Hypotheses: Does a new drug lower blood pressure more effectively than an existing one? Does exposure to violent video games affect aggression in children?
• Generalize Findings: Can we infer the opinions of an entire population based on a survey of a representative sample?

Market research exemplifies quantitative research in action. Companies use surveys to understand consumer preferences and habits, allowing them to adjust products and marketing.

Types of Quantitative Research Designs

Several types of quantitative research designs exist:

• Surveys: Surveys collect data from a sample using questionnaires or interviews. They can be administered online, by phone, or in person. Political polls are a common example.
• Experiments: Experiments manipulate variables (independent variables) to observe their impact on another variable (dependent variable). They aim to establish cause-and-effect relationships. Drug trials are a classic example.
• Correlational Studies: These studies examine the relationship between variables without manipulation. They can reveal patterns and associations, but not causality. For example, a correlation between ice cream sales and crime rates doesn't mean one causes the other.
• Descriptive Studies: Descriptive studies characterize a population or phenomenon without testing hypotheses or establishing relationships. An example might be documenting bird species in a specific habitat.

Data Analysis in Quantitative Research

Quantitative research relies on statistical analysis. Common techniques include:

• Descriptive Statistics: These summarize a dataset's main features using measures like mean, median, mode, and standard deviation.
• Inferential Statistics: These allow researchers to draw conclusions about a population from sample data, including hypothesis testing, confidence intervals, and regression analysis.

The appropriate statistical technique depends on your research question and data type. Using the correct methods ensures validity and reliability. By carefully choosing a quantitative methodology and applying rigorous statistical analysis, researchers can gain valuable insights.

Qualitative Research Methods

Let's now explore qualitative research methods. This methodology focuses on understanding the "why" behind the "what." Instead of quantifying, qualitative research explores how and why people think, feel, and act. It aims to provide nuanced insights into complex social issues that numbers alone can't capture. Think of it as creating a detailed painting rather than a quick sketch. While quantitative research might reveal that 60% of people prefer a certain coffee brand, qualitative research would explore why – is it the taste, the aroma, the brand image, or other factors?

When to Use Qualitative Research Methods

Qualitative methods are effective when exploring:

• Lived Experiences: What is it like to live with a chronic illness? How do immigrants adapt to a new culture?
• Meaning and Interpretation: How do people interpret their experiences? Which values and beliefs shape their behavior?
• Complex Social Processes: How do power dynamics influence decisions? How does social change happen?
• Hypothesis Generation: While quantitative research tests hypotheses, qualitative research can generate them by exploring a topic in depth, uncovering patterns and themes that lead to new research questions.

For example, to understand social media's impact on body image, a qualitative approach might involve interviewing young people to explore their experiences and perceptions, providing a deeper understanding of the complex relationship.

Types of Qualitative Research Designs

Qualitative research offers various research designs:

• Interviews: Interviews are one-on-one conversations that gather individual perspectives. They can be structured, semi-structured, or unstructured, offering varying levels of flexibility.
• Focus Groups: These are discussions with small groups, exploring shared experiences and perspectives. The group dynamic can generate unique insights.
• Ethnography: This involves immersing oneself in a culture or community to observe behavior and beliefs firsthand. This can include participant observation or non-participant observation. An anthropologist living with a remote tribe to study their customs is a classic example.
• Case Studies: Case studies involve detailed analysis of a single individual, group, or event, useful for understanding complex phenomena in context. A case study might examine a successful company to identify its growth factors.
• Content Analysis: This involves systematically analyzing existing texts, like documents or media reports, to identify patterns and themes. This can help understand how a topic is represented or explore public opinion.

Data Analysis in Qualitative Research

Qualitative research uses specific techniques to interpret data, often involving identifying patterns, themes, and meanings:

• Thematic Analysis: This involves identifying recurring themes and patterns, both explicit and implicit.
• Narrative Analysis: This focuses on the stories participants share, exploring how they construct their experiences.
• Discourse Analysis: This examines how language creates meaning and power dynamics, exploring how it shapes our understanding.
• Grounded Theory: This develops a theory based on the collected data through an iterative process of data collection and analysis.

By carefully choosing a qualitative methodology and applying rigorous analytical techniques, researchers can gain deep insights into complex social phenomena, providing perspectives quantitative methods often miss.

Data Collection Techniques

Having explored qualitative and quantitative research methods, let’s discuss data collection. This is where theory meets practice in research methodology. Your data collection methods directly affect the quality and dependability of your findings. Just as a chef chooses the best ingredients, a researcher must select the most appropriate techniques for their research question.

Matching Techniques to Methodology

The best data collection techniques depend on your chosen research methodology. For quantitative approaches, focusing on numerical data, you might use:

• Surveys: Questionnaires distributed widely can gather quantifiable data on attitudes, behaviors, and demographics. Online tools are cost-effective for reaching broad audiences, while paper surveys can target specific groups.
• Experiments: Controlled experiments allow researchers to manipulate variables and measure their impact, collecting data under different conditions to identify cause-and-effect relationships.
• Existing Datasets: Utilizing publicly available data from government agencies, research institutions, or even social media can be a valuable time- and resource-saving technique.

For qualitative research, aiming for rich descriptive data, you might choose:

• Interviews: In-depth interviews offer detailed narratives and perspectives. They can be structured, semi-structured, or unstructured, providing different levels of flexibility.
• Focus Groups: Similar to interviews, focus groups facilitate discussions with a group, providing insights into shared experiences. This interactive approach can generate unexpected insights.
• Observations: Directly observing behavior in natural settings provides contextualized data. This can include participant observation or non-participant observation.
• Document Analysis: Examining existing documents, such as letters, diaries, or media reports, provides insights into past events, social norms, and individual experiences. This is especially relevant in fields like history and sociology.

Ensuring Data Quality

Regardless of the chosen techniques, data quality is paramount. This involves considering:

• Reliability: Will repeated data collection yield consistent results?
• Validity: Are you measuring what you intend to measure? Does your data truly reflect the phenomenon you’re studying?
• Representativeness: Does your sample accurately represent the target population? Are your findings generalizable?

For example, to understand user experiences with software, combining user interviews, usability tests, and feedback surveys provides a more robust picture than website traffic data alone.

By carefully aligning your data collection with your methodology and prioritizing data quality, you create a solid foundation for analysis and ensure meaningful contributions to the field.

Research Ethics

Data collection, whether through quantitative surveys or qualitative interviews, is central to research methodology. However, it's vital to remember that research involves people, communities, and potentially sensitive information. Research ethics requires us to conduct our work responsibly, respecting participants' rights and well-being. Just as doctors pledge to "do no harm," researchers have an ethical obligation.

Core Principles of Ethical Research

Several core principles underpin ethical research:

• Informed Consent: Participants must be fully informed about the research purpose, their involvement, and data usage. They have the right to withdraw at any time without penalty. Participating in a privacy study and later discovering your data is sold to advertisers violates informed consent.
• Confidentiality and Anonymity: Researchers must protect participant privacy. Data should be stored securely, identities kept confidential, and, when possible, anonymized to remove identifying information. Protecting the identities of vulnerable populations, such as refugees or victims of abuse, is especially important.
• Minimizing Harm: Researchers should take steps to minimize any potential harm, including psychological harm (e.g., emotional distress) or physical harm. A study on bullying, for example, must be designed to avoid exacerbating the problem.
• Avoiding Deception: Researchers should be truthful about the research. Deception is permissible only in rare cases where absolutely necessary for the study and approved by an ethics review board. The Milgram experiment, which deceived participants about the study’s purpose, is a controversial example.
• Transparency and Accountability: Researchers should be transparent about their methods and findings, and accountable for ethical conduct. This includes being open to scrutiny from peers and the public.

Navigating Ethical Dilemmas

Even with clear guidelines, ethical dilemmas can arise. What if a researcher uncovers illegal activity during an interview? What if a participant requests data removal after the study’s completion? These situations require careful consideration and often consultation with an ethics review board or other experts.

Research ethics is not merely a checklist; it's integral to research methodology. Adhering to ethical principles ensures the integrity of your work and protects participants, leading to trustworthy results and contributing positively to knowledge.

Data Analysis and Interpretation

Having collected your data and navigated ethical considerations, you now have a large amount of information. What's next? This is where data analysis and interpretation, a critical part of your methodology, comes in. It's about transforming raw data into meaningful insights that answer your research question. Think of it as detective work: piecing together clues to reveal the bigger picture. Whether working with numbers, text, or images, the goal is to find significant patterns and draw valid conclusions.

Making Sense of the Data

Your approach to data analysis depends on your methodology. Quantitative approaches involve numerical data and statistical methods. This may include descriptive statistics (like means and standard deviations) to summarize data, or inferential statistics (like t-tests or regression analysis) to test hypotheses. For example, a researcher studying a marketing campaign’s effectiveness might compare sales figures before and after the campaign to determine its impact.

Qualitative data analysis is different. It involves textual, audio, or visual data, often from interviews, focus groups, or observations. The goal is to identify themes, patterns, and meanings. This might involve coding transcripts to categorize responses, finding recurring ideas, or analyzing interview narratives. For example, a researcher studying consumer perceptions of a new product might analyze interview transcripts for common themes in feedback.

Interpretation: Connecting the Dots

Data analysis is only the first step. Interpretation involves connecting the dots and explaining the significance of your findings. This means moving beyond simply describing what the data shows to explaining why it matters. Relate your findings to your research question, discuss their implications, and draw conclusions. A well-designed methodology is crucial for ensuring valid interpretations. Just as a historian carefully contextualizes evidence, a researcher must consider the limitations of their data and avoid overgeneralizing. If a study finds a correlation between two variables, the researcher must not assume a causal relationship without further investigation.

Communicating Your Findings

The final stage is communicating your findings. This could involve writing a report, presenting at a conference, or creating a visual representation. Clear communication is essential for your research to have an impact. A scientist presenting at a conference must clearly communicate their methodology, findings, and implications to their peers. Effective communication includes presenting the data clearly, acknowledging limitations, and suggesting areas for future research.

By following a rigorous methodology, thoroughly analyzing your data, and carefully interpreting your findings, you can transform raw information into valuable insights.

We've explored the key elements of research methodology, from formulating research questions to interpreting data. Whether conducting a quantitative study measuring the effectiveness of a teaching method or a qualitative exploration of lived experiences, a well-defined methodology is essential for achieving reliable and meaningful results. Just as an architect needs a blueprint, a researcher needs a carefully considered methodology.

Key Takeaways: Building a Strong Research Foundation

• The Right Tool for the Job: Choosing the right methodology—qualitative, quantitative, or mixed methods—depends entirely on your research question.
• Data Collection Done Right: Your data collection techniques must align with your chosen methodology and meet standards of reliability and validity.
• Ethics Matter: Research requires ethical conduct, respecting participants' rights. Informed consent, confidentiality, and minimizing harm are fundamental.
• Analysis and Interpretation: Data analysis transforms raw information into meaningful insights. The process varies depending on whether you’re using quantitative or qualitative data.
• Communication is Key: Sharing your findings clearly is essential, ensuring your work contributes to the body of knowledge.

Developing a robust research methodology is an ongoing process. It involves making informed decisions at each stage, ensuring your study is well-designed, ethical, and contributes significantly to your field.

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