15 Types of Research Methods

Research methods refer to the strategies, tools, and techniques used to gather and analyze data in a structured way in order to answer a research question or investigate a hypothesis (Hammond & Wellington, 2020).

Generally, we place research methods into two categories: quantitative and qualitative. Each has its own strengths and weaknesses, which we can summarize as:

• Quantitative research can achieve generalizability through scrupulous statistical analysis applied to large sample sizes.
• Qualitative research achieves deep, detailed, and nuance accounts of specific case studies, which are not generalizable.

Some researchers, with the aim of making the most of both quantitative and qualitative research, employ mixed methods, whereby they will apply both types of research methods in the one study, such as by conducting a statistical survey alongside in-depth interviews to add context to the quantitative findings.

Below, I’ll outline 15 common research methods, and include pros, cons, and examples of each.

Types of Research Methods

Research methods can be broadly categorized into two types: quantitative and qualitative.

• Quantitative methods involve systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques, providing an in-depth understanding of a specific concept or phenomenon (Schweigert, 2021). The strengths of this approach include its ability to produce reliable results that can be generalized to a larger population, although it can lack depth and detail.
• Qualitative methods encompass techniques that are designed to provide a deep understanding of a complex issue, often in a specific context, through collection of non-numerical data (Tracy, 2019). This approach often provides rich, detailed insights but can be time-consuming and its findings may not be generalizable.

These can be further broken down into a range of specific research methods and designs:

Primarily Quantitative Methods	Primarily Qualitative methods
Experimental Research	Case Study
Surveys and Questionnaires	Ethnography
Longitudinal Studies	Phenomenology
Cross-Sectional Studies	Historical research
Correlational Research	Content analysis
Causal-Comparative Research	Grounded theory
Meta-Analysis	Action research
Quasi-Experimental Design	Observational research

Combining the two methods above, mixed methods research mixes elements of both qualitative and quantitative research methods, providing a comprehensive understanding of the research problem. We can further break these down into:

• Sequential Explanatory Design (QUAN→QUAL): This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.
• Sequential Exploratory Design (QUAL→QUAN): This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

Let’s explore some methods and designs from both quantitative and qualitative traditions, starting with qualitative research methods.

Qualitative Research Methods

Qualitative research methods allow for the exploration of phenomena in their natural settings, providing detailed, descriptive responses and insights into individuals’ experiences and perceptions (Howitt, 2019).

These methods are useful when a detailed understanding of a phenomenon is sought.

1. Ethnographic Research

Ethnographic research emerged out of anthropological research, where anthropologists would enter into a setting for a sustained period of time, getting to know a cultural group and taking detailed observations.

Ethnographers would sometimes even act as participants in the group or culture, which many scholars argue is a weakness because it is a step away from achieving objectivity (Stokes & Wall, 2017).

In fact, at its most extreme version, ethnographers even conduct research on themselves, in a fascinating methodology call autoethnography.

The purpose is to understand the culture, social structure, and the behaviors of the group under study. It is often useful when researchers seek to understand shared cultural meanings and practices in their natural settings.

However, it can be time-consuming and may reflect researcher biases due to the immersion approach.

Pros of Ethnographic Research	Cons of Ethnographic Research
1. Provides deep cultural insights	1. Time-consuming
2. Contextually relevant findings	2. Potential researcher bias
3. Explores dynamic social processes	3. May raise ethical issues

2. Phenomenological Research

Phenomenological research is a qualitative method focused on the study of individual experiences from the participant’s perspective (Tracy, 2019).

It focuses specifically on people’s experiences in relation to a specific social phenomenon (see here for examples of social phenomena).

This method is valuable when the goal is to understand how individuals perceive, experience, and make meaning of particular phenomena. However, because it is subjective and dependent on participants’ self-reports, findings may not be generalizable, and are highly reliant on self-reported ‘thoughts and feelings’.

Pros of Phenomenological Research	Cons of Phenomenological Research
1. Provides rich, detailed data	1. Limited generalizability
2. Highlights personal experience and perceptions	2. Data collection can be time-consuming
3. Allows exploration of complex phenomena	3. Requires highly skilled researchers

3. Historical Research

Historical research is a qualitative method involving the examination of past events to draw conclusions about the present or make predictions about the future (Stokes & Wall, 2017).

As you might expect, it’s common in the research branches of history departments in universities.

This approach is useful in studies that seek to understand the past to interpret present events or trends. However, it relies heavily on the availability and reliability of source materials, which may be limited.

Common data sources include cultural artifacts from both material and non-material culture, which are then examined, compared, contrasted, and contextualized to test hypotheses and generate theories.

Pros of Historical Research	Cons of Historical Research
1. Provides historical context	1. Dependent on available sources
2. Can help understand current events or trends	2. Potential bias in source materials
3. Allows the study of change over time	3. Difficult to replicate

4. Content Analysis

Content analysis is a research method that involves systematic and objective coding and interpreting of text or media to identify patterns, themes, ideologies, or biases (Schweigert, 2021).

A content analysis is useful in analyzing communication patterns, helping to reveal how texts such as newspapers, movies, films, political speeches, and other types of ‘content’ contain narratives and biases.

However, interpretations can be very subjective, which often requires scholars to engage in practices such as cross-comparing their coding with peers or external researchers.

Content analysis can be further broken down in to other specific methodologies such as semiotic analysis, multimodal analysis, and discourse analysis.

Pros of Content Analysis	Cons of Content Analysis
1. Unobtrusive data collection	1. Lacks contextual information
2. Allows for large sample analysis	2. Potential coder bias
3. Replicable and reliable if done properly	3. May overlook nuances

5. Grounded Theory Research

Grounded theory involves developing a theory during and after data collection rather than beforehand.

This is in contrast to most academic research studies, which start with a hypothesis or theory and then testing of it through a study, where we might have a null hypothesis (disproving the theory) and an alternative hypothesis (supporting the theory).

Grounded Theory is useful because it keeps an open mind to what the data might reveal out of the research. It can be time-consuming and requires rigorous data analysis (Tracy, 2019).

Pros of Grounded Theory Research	Cons of Grounded Theory Research
1. Helps with theory development	1. Time-consuming
2. Rigorous data analysis	2. Requires iterative data collection and analysis
3. Can fill gaps in existing theories	3. Requires skilled researchers

6. Action Research

Action research is an approach which aims to solve real-world problems and bring about change within a setting. The study is designed to solve a specific problem – or in other words, to take action (Patten, 2017).

This approach can involve mixed methods, but is generally qualitative because it usually involves the study of a specific case study wherein the researcher works, e.g. a teacher studying their own classroom practice to seek ways they can improve.

Action research is very common in fields like education and nursing where practitioners identify areas for improvement then implement a study in order to find paths forward.

Pros of Action Research	Cons of Action Research
1. Addresses real-world problems and seeks to find solutions.	1. It is time-consuming and often hard to implement into a practitioner’s already busy schedule
2. Integrates research and action in an action-research cycle.	2. Requires collaboration between researcher, practitioner, and research participants.
3. Can bring about positive change in isolated instances, such as in a school or nursery setting.	3. Complexity of managing dual roles (where the researcher is also often the practitioner)

7. Natural Observational Research

Observational research can also be quantitative (see: experimental research), but in naturalistic settings for the social sciences, researchers tend to employ qualitative data collection methods like interviews and field notes to observe people in their day-to-day environments.

This approach involves the observation and detailed recording of behaviors in their natural settings (Howitt, 2019). It can provide rich, in-depth information, but the researcher’s presence might influence behavior.

While observational research has some overlaps with ethnography (especially in regard to data collection techniques), it tends not to be as sustained as ethnography, e.g. a researcher might do 5 observations, every second Monday, as opposed to being embedded in an environment.

Pros of Qualitative Observational Research	Cons of Qualitative Observational Research
1. Captures behavior in natural settings, allowing for interesting insights into authentic behaviors.	1. Researcher’s presence may influence behavior
2. Can provide rich, detailed data through the researcher’s vignettes.	2. Can be time-consuming
3. Non-invasive because researchers want to observe natural activities rather than interfering with research participants.	3. Requires skilled and trained observers

8. Case Study Research

Case study research is a qualitative method that involves a deep and thorough investigation of a single individual, group, or event in order to explore facets of that phenomenon that cannot be captured using other methods (Stokes & Wall, 2017).

Case study research is especially valuable in providing contextualized insights into specific issues, facilitating the application of abstract theories to real-world situations (Patten, 2017).

However, findings from a case study may not be generalizable due to the specific context and the limited number of cases studied (Walliman, 2021).

Pros of Case Study Research	Cons of Case Study Research
1. Provides detailed insights	1. Limited generalizability
2. Facilitates the study of complex phenomena	2. Can be time-consuming
3. Can test or generate theories	3. Subject to observer bias

See More: Case Study Advantages and Disadvantages

Quantitative Research Methods

Quantitative research methods involve the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques (Pajo, 2022). The focus is on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

9. Experimental Research

Experimental research is a quantitative method where researchers manipulate one variable to determine its effect on another (Walliman, 2021).

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

This type of research is useful in situations where researchers want to determine causal relationships between variables. However, experimental conditions may not reflect real-world conditions.

Pros of Experimental Research	Cons of Experimental Research
1. Allows for determination of causality	1. Might not reflect real-world conditions
2. Allows for the study of phenomena in highly controlled environments to minimize research contamination.	2. Can be costly and time-consuming to create a controlled environment.
3. Can be replicated so other researchers can test and verify the results.	3. Ethical concerns need to be addressed as the research is directly manipulating variables.

10. Surveys and Questionnaires

Surveys and questionnaires are quantitative methods that involve asking research participants structured and predefined questions to collect data about their attitudes, beliefs, behaviors, or characteristics (Patten, 2017).

Surveys are beneficial for collecting data from large samples, but they depend heavily on the honesty and accuracy of respondents.

They tend to be seen as more authoritative than their qualitative counterparts, semi-structured interviews, because the data is quantifiable (e.g. a questionnaire where information is presented on a scale from 1 to 10 can allow researchers to determine and compare statistical means, averages, and variations across sub-populations in the study).

Pros of Surveys and Questionnaires	Cons of Surveys and Questionnaires
1. Data can be gathered from larger samples than is possible in qualitative research.	1. There is heavy dependence on respondent honesty
2. The data is quantifiable, allowing for comparison across subpopulations	2. There is limited depth of response as opposed to qualitative approaches.
3. Can be cost-effective and time-efficient	3. Static with no flexibility to explore responses (unlike semi- or unstrcutured interviewing)

11. Longitudinal Studies

Longitudinal studies involve repeated observations of the same variables over extended periods (Howitt, 2019). These studies are valuable for tracking development and change but can be costly and time-consuming.

With multiple data points collected over extended periods, it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes a detailed analysis of change possible.

Perhaps the most relatable example of a longitudinal study is a national census, which is taken on the same day every few years, to gather comparative demographic data that can show how a nation is changing over time.

While longitudinal studies are commonly quantitative, there are also instances of qualitative ones as well, such as the famous 7 Up study from the UK, which studies 14 individuals every 7 years to explore their development over their lives.

Pros of Longitudinal Studies	Cons of Longitudinal Studies
1. Tracks changes over time allowing for comparison of past to present events.	1. Is almost by definition time-consuming because time needs to pass between each data collection session.
2. Can identify sequences of events, but causality is often harder to determine.	2. There is high risk of participant dropout over time as participants move on with their lives.

12. Cross-Sectional Studies

Cross-sectional studies are a quantitative research method that involves analyzing data from a population at a specific point in time (Patten, 2017). They provide a snapshot of a situation but cannot determine causality.

This design is used to measure and compare the prevalence of certain characteristics or outcomes in different groups within the sampled population.

The major advantage of cross-sectional design is its ability to measure a wide range of variables simultaneously without needing to follow up with participants over time.

However, cross-sectional studies do have limitations. This design can only show if there are associations or correlations between different variables, but cannot prove cause and effect relationships, temporal sequence, changes, and trends over time.

Pros of Cross-Sectional Studies	Cons of Cross-Sectional Studies
1. Quick and inexpensive, with no long-term commitment required.	1. Cannot determine causality because it is a simple snapshot, with no time delay between data collection points.
2. Good for descriptive analyses.	2. Does not allow researchers to follow up with research participants.

13. Correlational Research

Correlational research is a quantitative method that seeks to determine if and to what degree a relationship exists between two or more quantifiable variables (Schweigert, 2021).

This approach provides a fast and easy way to make initial hypotheses based on either positive or negative correlation trends that can be observed within dataset.

While correlational research can reveal relationships between variables, it cannot establish causality.

Methods used for data analysis may include statistical correlations such as Pearson’s or Spearman’s.

Pros of Correlational Research	Cons of Correlational Research
1. Reveals relationships between variables	1. Cannot determine causality
2. Can use existing data	2. May be influenced by third variables
3. Can guide further experimental research	3. Correlation may be coincidental

14. Quasi-Experimental Design Research

Quasi-experimental design research is a quantitative research method that is similar to experimental design but lacks the element of random assignment to treatment or control.

Instead, quasi-experimental designs typically rely on certain other methods to control for extraneous variables.

The term ‘quasi-experimental’ implies that the experiment resembles a true experiment, but it is not exactly the same because it doesn’t meet all the criteria for a ‘true’ experiment, specifically in terms of control and random assignment.

Quasi-experimental design is useful when researchers want to study a causal hypothesis or relationship, but practical or ethical considerations prevent them from manipulating variables and randomly assigning participants to conditions.

Pros of Quasi-Experimental Research	Cons of Quasi-Experimental Research
1. It’s more feasible to implement than true experiments.	1. Without random assignment, it’s harder to rule out confounding variables.
2. It can be conducted in real-world settings, making the findings more applicable to the real world.	2. The lack of random assignment may reduce the internal validity of the study.
3. Useful when it’s unethical or impossible to manipulate the independent variable or randomly assign participants.	3. It’s more difficult to establish a cause-effect relationship due to the potential for confounding variables.

Related: Examples and Types of Random Assignment in Research

15. Meta-Analysis Research

Meta-analysis statistically combines the results of multiple studies on a specific topic to yield a more precise estimate of the effect size. It’s the gold standard of secondary research.

Meta-analysis is particularly useful when there are numerous studies on a topic, and there is a need to integrate the findings to draw more reliable conclusions.

Some meta-analyses can identify flaws or gaps in a corpus of research, when can be highly influential in academic research, despite lack of primary data collection.

However, they tend only to be feasible when there is a sizable corpus of high-quality and reliable studies into a phenomenon.

Pros of Meta-Analysis Research	Cons of Meta-Analysis Research
Increased Statistical Power: By combining data from multiple studies, meta-analysis increases the statistical power to detect effects.	Publication Bias: Studies with null or negative findings are less likely to be published, leading to an overestimation of effect sizes.
Greater Precision: It provides more precise estimates of effect sizes by reducing the influence of random error.	Quality of Studies: The accuracy of a meta-analysis depends on the quality of the studies included.
Resolving Discrepancies: Meta-analysis can help resolve disagreements between different studies on a topic.	Heterogeneity: Differences in study design, sample, or procedures can introduce heterogeneity, complicating interpretation of results.

Conclusion

Choosing a research method requires a lot of consideration regarding what you want to achieve, your research paradigm, and the methodology that is most valuable for what you are studying. There are multiple types of research methods, many of which I haven’t been able to present here. Generally, it’s recommended that you work with an experienced researcher or research supervisor to identify a suitable research method for your study at hand.

References

Hammond, M., & Wellington, J. (2020). Research methods: The key concepts. New York: Routledge.

Howitt, D. (2019). Introduction to qualitative research methods in psychology. London: Pearson UK.

Pajo, B. (2022). Introduction to research methods: A hands-on approach. New York: Sage Publications.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials. New York: Sage

Schweigert, W. A. (2021). Research methods in psychology: A handbook. Los Angeles: Waveland Press.

Stokes, P., & Wall, T. (2017). Research methods. New York: Bloomsbury Publishing.

Tracy, S. J. (2019). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact. London: John Wiley & Sons.

Walliman, N. (2021). Research methods: The basics. London: Routledge.