In brief
- The methods section describes your design, participants, materials, procedure and analysis in enough detail for someone to replicate or evaluate the study.
- Write it in the past tense and justify each choice briefly, citing established methods.
- Quantitative methods sections report sampling, measures, reliability and statistical tests; qualitative ones also report the researcher's role and trustworthiness.
- Reporting standards such as APA JARS, CONSORT, STROBE and COREQ tell you what reviewers expect to see.
What is the methods section of a research paper? ¶
The methods section (also called methodology, or materials and methods) explains how you conducted your study: the research design, who or what you studied, how you collected data, and how you analyzed it. Its job is transparency. A reader should be able to evaluate whether your methods can answer your research question and, in principle, repeat the study.
The terms are often used loosely, but there is a distinction worth knowing. Methods are the specific procedures and tools you used (a survey, interviews, a regression model). Methodology is the reasoning behind those choices, including your philosophical stance and why this design suits this question. A journal article usually has a concise "Method" section; a thesis often has a full "Methodology" chapter that covers both.
In APA style the heading is singular: Method. Many other journals use Methods or Materials and Methods; follow the author guidelines of your target journal or program.
What to include in a methods section ¶
The exact subsections depend on your field and design. These are the common building blocks, broadly following the APA Journal Article Reporting Standards (JARS).
| Subsection | What to report |
|---|---|
| Research design | The overall design (experimental, cross-sectional survey, case study, ethnography, explanatory sequential mixed methods) and why it fits the question. |
| Participants or sample | Population, inclusion and exclusion criteria, sampling method, recruitment, sample size and its justification, and key demographics. |
| Materials and measures | Instruments, questionnaires, equipment or interview guides, with sources, scoring and reliability or validity evidence. |
| Procedure | What happened, in order: setting, dates, steps, instructions, duration, any randomization or blinding. |
| Data analysis | Software and version, statistical tests or qualitative analytic approach, assumption checks, handling of missing data. |
| Ethics | Ethics committee or IRB approval, informed consent, confidentiality and data storage. |
Qualitative studies add the researcher's position (reflexivity) and the steps taken for trustworthiness, such as reflexive journals, peer debriefing or an audit trail.
How to write a methods section: 6 practical rules ¶
- Write in the past tense. "Participants completed...", "Interviews were transcribed...". Describe what you did, not what you planned (a proposal uses the future tense).
- Give enough detail to replicate, and no more. Cite a published protocol or instrument instead of describing it in full. Put long materials in an appendix.
- Justify key choices in a sentence. Say why you chose this sample size, this instrument or this analysis.
- Follow a logical order. Design, then participants, then measures, then procedure, then analysis.
- Use subheadings. In APA style, the section heading "Method" is Level 1 and subsections such as "Participants" are Level 2.
- Keep results out. Report descriptive characteristics of the sample here if your field expects it, but save findings for the Results section.
Write the methods section first. It is the easiest part to draft while the details are fresh, and it often reveals gaps you need to fix before analysis.
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Quantitative methodology example ¶
This sample methods section is for a hypothetical cross-sectional survey testing whether workload and social support predict depressive symptoms in nurses. The numbers belong to the illustrative study.
Quantitative example (APA style)
Design
We used a cross-sectional online survey design.
Participants
Registered nurses working at least 20 hours per week in three public hospitals were eligible. An a priori power analysis in G*Power 3.1 for multiple regression with three predictors (f² = 0.15, α = .05, power = .80) indicated a minimum sample of 77. Of 412 nurses invited by email, 186 completed the survey (response rate 45.1%). Participants were aged 22 to 61 years (M = 36.4, SD = 9.8), and 81.2% identified as women.
Measures
Depressive symptoms were measured with the Patient Health Questionnaire-9 (PHQ-9; Kroenke et al., 2001), which scores nine items from 0 (not at all) to 3 (nearly every day), giving totals from 0 to 27. Internal consistency in this sample was good (Cronbach's α = .87). Workload and social support were measured with validated subscales described in Appendix A.
Procedure
The survey was open for 4 weeks in March 2025 on Qualtrics. Participation was anonymous and voluntary. The study was approved by the university research ethics committee, and all participants gave informed consent online.
Data Analysis
Analyses were conducted in IBM SPSS Statistics (Version 29). We tested the hypotheses with multiple linear regression, entering workload, social support and years of experience as predictors. Assumptions of linearity, normality of residuals, homoscedasticity and absence of multicollinearity (all VIFs < 2) were checked. Less than 2% of item responses were missing and were handled by person-mean imputation within scales.
For more on this design, see our guide to the cross-sectional study. If you want help choosing or checking your analysis, our statistics consulting works through it with you and explains the output so you can report it yourself.
Qualitative methodology example ¶
Here is a sample qualitative methods section for an interview study. Note the attention to sampling logic, the researcher's role and trustworthiness.
Qualitative example (APA style)
Design and Approach
This study used a qualitative descriptive design with semi-structured interviews to explore how early-career teachers experience their first year in rural schools. It was informed by an interpretivist stance, which assumes that meaning is constructed through participants' experiences.
Participants and Recruitment
We used purposive sampling to recruit teachers in their first or second year at rural public schools, seeking variation in subject, gender and school size. Recruitment through two regional teacher networks yielded 18 participants. Recruitment stopped when later interviews added little new insight relevant to the research question.
Data Collection
Interviews lasted 45 to 70 minutes and were conducted on Zoom between January and April 2025, using a guide with open questions on workload, support and belonging (Appendix B). Interviews were audio-recorded with consent and transcribed verbatim.
Data Analysis
We used reflexive thematic analysis (Braun & Clarke, 2006): familiarization, generating initial codes, constructing themes, reviewing themes, defining and naming themes, and writing up. Coding was managed in NVivo 14.
Reflexivity and Trustworthiness
The first author is a former rural teacher, which aided rapport but could shape interpretation. She kept a reflexive journal, and the team met regularly to discuss and challenge emerging themes. An audit trail documented analytic decisions.
Ethics
The study received university ethics approval. Participants gave written consent and are identified by pseudonyms.
For a closer look at the coding stage, read our guide to thematic coding.
Method Research Design - Design type and why it fits the research question Participants (or Sample / Data Sources) - Population, inclusion and exclusion criteria - Sampling method and recruitment - Sample size and justification (power analysis or sampling logic) - Key characteristics of the final sample Materials and Measures - Each instrument: source, items, scoring, reliability/validity Procedure - Setting, dates, steps in order, duration - Randomization, blinding or interview process Data Analysis - Software and version - Tests or analytic approach; assumption checks; missing data - (Qualitative) reflexivity and trustworthiness strategies Ethical Considerations - Approving committee, consent, confidentiality, data storage
Mixed methods methodology example ¶
Mixed methods sections must also explain how and when the two strands are integrated.
Mixed methods example
Design
We used an explanatory sequential mixed methods design. In Phase 1, a survey of 240 university students measured sense of belonging and intention to continue studying. In Phase 2, we interviewed 14 survey respondents, selected because their belonging scores were unusually high or low, to explain the quantitative patterns.
Integration
Integration occurred at two points. Phase 1 results guided participant selection and the interview guide for Phase 2. After both analyses, we compared findings in a joint display that set statistical results beside the related qualitative themes, noting where they confirmed, expanded or contradicted each other.
Analysis
Survey data were analyzed with hierarchical regression in R (Version 4.4). Interview data were analyzed thematically. Meta-inferences were drawn from the joint display.
Reporting guidelines for methods sections ¶
Many journals require you to follow a reporting guideline and submit its checklist. The EQUATOR Network collects them. The most common:
| Study type | Guideline |
|---|---|
| Quantitative, qualitative and mixed methods research in psychology and social sciences | APA JARS (JARS–Quant, JARS–Qual, JARS–Mixed) |
| Randomized controlled trials | CONSORT |
| Observational studies (cohort, case-control, cross-sectional) | STROBE |
| Qualitative interviews and focus groups | COREQ or SRQR |
| Systematic reviews | PRISMA 2020 |
Checking your draft against the right checklist is the quickest way to spot missing details before a reviewer does.
Common methods section mistakes ¶
- Too little detail on the sample. State how participants were recruited and how many were invited, excluded and retained.
- No justification for sample size. Report a power analysis for quantitative work, or the sampling logic for qualitative work.
- Instruments without reliability or source. Cite each scale and report reliability in your own sample.
- Vague analysis. "Data were analyzed statistically" is not enough. Name the tests, software and version.
- Missing ethics statement. Include the approving body and how consent was obtained.
A methods chapter is where supervisors and examiners probe hardest. Our dissertation help offers field-matched feedback and coaching on your methodology chapter, with comments that explain each point while the work stays yours. Start from a clear question, too; our research question examples show how question wording predicts design.