How to write an APA methods section

The methods section of an APA style paper is where you report in detail how you performed your study. Research papers in the social and natural sciences often follow APA style. This article focuses on reporting quantitative research methods.

In your APA methods section, you should report enough information to understand and replicate your study, including detailed information on the sample, measures, and procedures used.

Structuring an APA methods section

The main heading of “Methods” should be centered, boldfaced, and capitalized. Subheadings within this section are left-aligned, boldfaced, and in title case. You can also add lower level headings within these subsections, as long as they follow APA heading styles.

To structure your methods section, you can use the subheadings of “Participants,” “Materials,” and “Procedures.” These headings are not mandatory—aim to organize your methods section using subheadings that make sense for your specific study.

Heading What to include
  • Participant or subject characteristics
  • Sampling procedures
  • Sample size and power
  • Primary and secondary measures
  • Quality of measurements
  • Data collection methods
  • Research design (e.g., experimental, correlational, or descriptive)
  • Data processing and diagnostics (e.g., outlier removal)
  • Data analysis strategy (e.g., comparison or regression tests)

Note that not all of these topics will necessarily be relevant for your study. For example, if you didn’t need to consider outlier removal or ways of assigning participants to different conditions, you don’t have to report these steps.

The APA also provides specific reporting guidelines for different types of research design. These tell you exactly what you need to report for longitudinal designs, replication studies, experimental designs, and so on. If your study uses a combination design, consult APA guidelines for mixed methods studies.

Detailed descriptions of procedures that don’t fit into your main text can be placed in supplemental materials (for example, the exact instructions and tasks given to participants, the full analytical strategy including software code, or additional figures and tables).


Begin the methods section by reporting sample characteristics, sampling procedures, and the sample size.

Participant or subject characteristics

When discussing people who participate in research, descriptive terms like “participants,” “subjects” and “respondents” can be used. For non-human animal research, “subjects” is more appropriate.

Specify all relevant demographic characteristics of your participants. This may include their age, sex, ethnic or racial group, gender identity, education level, and socioeconomic status. Depending on your study topic, other characteristics like educational or immigration status or language preference may also be relevant.

Be sure to report these characteristics as precisely as possible. This helps the reader understand how far your results may be generalized to other people.

The APA guidelines emphasize writing about participants using bias-free language, so it’s necessary to use inclusive and appropriate terms.

Example: Reporting participant characteristics
The participants included 134 cisgender men between 18 and 25 years old from a public university in New York. All participants were right-handed, fluent in English, and first-generation college students.

Sampling procedures

Outline how the participants were selected and all inclusion and exclusion criteria applied. Appropriately identify the sampling procedure used. For example, you should only label a sample as random if you had access to every member of the relevant population.

Of all the people invited to participate in your study, note the percentage that actually did (if you have this data). Additionally, report whether participants were self-selected, either by themselves or by their institutions (e.g., schools may submit student data for research purposes).

Identify any compensation (e.g., course credits or money) that was provided to participants, and mention any institutional review board approvals and ethical standards followed.

Example: Reporting sampling procedures
Ethics approval was obtained before we began recruiting participants. Current first-generation college students were invited to participate. The study was advertised through general emails sent to university-wide mailing lists, social media posts, and flyers across campus. Participants were self-selected and compensated $10 for their time in the hour-long study.

Sample size and power

Detail the sample size (per condition) and statistical power that you hoped to achieve, as well as any analyses you performed to determine these numbers.

It’s important to show that your study had enough statistical power to find effects if there were any to be found.

Additionally, state whether your final sample differed from the intended sample. Your interpretations of the study outcomes should be based only on your final sample rather than your intended sample.

Example: Reporting sample size and power
For our study to have 80% power to detect an effect of 10%, with a significance level of .05, 30 participants were required in each of the two conditions. The final sample satisfied these requirements.

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Write up the tools and techniques that you used to measure relevant variables. Be as thorough as possible for a complete picture of your techniques.

Primary and secondary measures

Define the primary and secondary outcome measures that will help you answer your primary and secondary research questions.

Specify all instruments used in gathering these measurements and the construct that they measure. These instruments may include hardware, software, or tests, scales, and inventories.

  • To cite hardware, indicate the model number and manufacturer.
  • To cite common software (e.g., Qualtrics), state the full name along with the version number or the website URL.
  • To cite tests, scales or inventories, reference its manual or the article it was published in. It’s also helpful to state the number of items and provide one or two example items.

Make sure to report the settings of (e.g., screen resolution) any specialized apparatus used.

For each instrument used, report measures of the following:

  • Reliability: how consistently the method measures something, in terms of internal consistency or test-retest reliability.
  • Validity: how precisely the method measures something, in terms of construct or criterion validity.

Giving an example item or two for surveys, questionnaires, and interviews is also helpful.

Example: Reporting materials
The Academic Anxiety Inventory (AAI; Pizzie & Kraemer, 2017) was used to measure academic anxiety in college students. The inventory consists of 50 Likert scale questions with subscales for math, science, and test anxiety. The participants indicated their level of agreement with statements on a 5-point scale ranging from “strongly disagree” to “strongly agree.” An example item is “I feel anxious when studying for a final.” Cronbach’s alpha was high (above .85) for each subscale, indicating sufficient internal consistency.

A general knowledge test appropriate for adults was created using materials from a previous study (see supplementary materials). The test consisted of 20 multiple choice questions with medium difficulty.

Describe any covariates—these are any additional variables that may explain or predict the outcomes.

Quality of measurements

Review all methods you used to assure the quality of your measurements.

These may include:

  • training researchers to collect data reliably,
  • using multiple people to assess (e.g., observe or code) the data,
  • translation and back-translation of research materials,
  • using pilot studies to test your materials on unrelated samples.

For data that’s subjectively coded (for example, classifying open-ended responses), report interrater reliability scores. This tells the reader how similarly each response was rated by multiple raters.


Report all of the procedures applied for administering the study, processing the data, and for planned data analyses.

Data collection methods and research design

Data collection methods refers to the general mode of the instruments: surveys, interviews, observations, focus groups, neuroimaging, cognitive tests, and so on. Summarize exactly how you collected the necessary data.

Describe all procedures you applied in administering surveys, tests, physical recordings, or imaging devices, with enough detail so that someone else can replicate your techniques. If your procedures are very complicated and require long descriptions (e.g., in neuroimaging studies), place these details in supplementary materials.

To report research design, note your overall framework for data collection and analysis. State whether you used an experimental, quasi-experimental, descriptive (observational), correlational, and/or longitudinal design. Also note whether a between-subjects or a within-subjects design was used.

For multi-group studies, report the following design and procedural details as well:

  • how participants were assigned to different conditions (e.g., randomization),
  • instructions given to the participants in each group,
  • interventions for each group,
  • the setting and length of each session(s).

Describe whether any masking was used to hide the condition assignment (e.g., placebo or medication condition) from participants or research administrators. Using masking in a multi-group study ensures internal validity by reducing bias. Explain how this masking was applied and whether its effectiveness was assessed.

Example: Reporting data collection methods and research design
All participants were told that the survey concerned students’ general knowledge and would take a maximum of thirty minutes. After arriving at the laboratory individually, they were assured confidentiality, and they provided informed consent.

Participants were randomly assigned to a control or experimental condition. The survey was administered using Qualtrics ( To begin, all participants were given the AAI and a demographics questionnaire to complete, followed by an unrelated filler task. In the control condition, participants completed a short general knowledge test immediately after the filler task. In the experimental condition, participants were asked to visualize themselves taking the test for 3 minutes before they actually did. For more details on the exact instructions and tasks given, see supplementary materials.

In the between-subjects experimental design, the independent variable was whether the visualization intervention was applied and the dependent variable was the difference in test scores between conditions.

Data diagnostics

Outline all steps taken to scrutinize or process the data after collection.

This includes the following:

  • procedures for identifying and removing outliers,
  • data transformations to normalize distributions,
  • compensation strategies for overcoming missing values.

To ensure high validity, you should provide enough detail for your reader to understand how and why you processed or transformed your raw data in these specific ways.

Analytic strategies

The methods section is also where you describe your statistical analysis procedures, but not their outcomes. Their outcomes are reported in the results section.

These procedures should be stated for all primary, secondary, and exploratory hypotheses. While primary and secondary hypotheses are based on a theoretical framework or past studies, exploratory hypotheses are guided by the data you’ve just collected.

Example: Reporting analytical strategy
First, we assessed whether there were any baseline differences between the two groups in terms of demographics characteristics or AAI scores. Subsequently, to test our primary hypothesis that the visualization intervention improves test performance, we performed an independent samples t test on test scores.

Example of an APA methods section

This annotated example reports methods for a descriptive correlational survey on the relationship between religiosity and trust in science in the US. Hover over each part for explanation of what is included.

Example of an APA methods section



The sample included 879 adults aged between 18-28. More than half of the participants were women (56%), and all participants had completed at least 12 years of education. Ethics approval was obtained from the university board before recruitment began. Participants were recruited online through Amazon Mechanical Turk (MTurk; We selected for a geographically diverse sample within the Midwest of the US through an initial screening survey. Participants were paid USD $5 upon completion of the study.

A sample size of at least 783 was deemed necessary for detecting a correlation coefficient of ±.1, with a power level of 80% and a significance level of .05, using a sample size calculator (


The primary outcome measures were the levels of religiosity and trust in science. Religiosity refers to involvement and belief in religious traditions, while trust in science represents confidence in scientists and scientific research outcomes. The secondary outcome measures were gender and parental education levels of participants and whether these characteristics predicted religiosity levels.


Religiosity was measured using the Centrality of Religiosity scale (Huber, 2003). The Likert scale is made up of 15 questions with five subscales of ideology, experience, intellect, public practice, and private practice. An example item is “How often do you experience situations in which you have the feeling that God or something divine intervenes in your life?” Participants were asked to indicate frequency of occurrence by selecting a response ranging from 1 (very often) to 5 (never). The internal consistency of the instrument is .83 (Huber & Huber, 2012).

Trust in Science

Trust in science was assessed using the General Trust in Science index (McCright, Dentzman, Charters & Dietz, 2013). Four Likert scale items were assessed on a scale from 1 (completely distrust) to 5 (completely trust). An example question asks “How much do you distrust or trust scientists to create knowledge that is unbiased and accurate?” Internal consistency was .8.


Potential participants were invited to participate in the survey online using Qualtrics ( The survey consisted of multiple choice questions regarding demographic characteristics, the Centrality of Religiosity scale, an unrelated filler anagram task, and finally the General Trust in Science index. The filler task was included to avoid priming or demand characteristics, and an attention check was embedded within the religiosity scale. For full instructions and details of tasks, see supplementary materials.

For this correlational study, we assessed our primary hypothesis of a relationship between religiosity and trust in science using Pearson moment correlation coefficient. The statistical significance of the correlation was assessed using a t test. To test our secondary hypothesis of parental education levels and gender as predictors of religiosity, multiple linear regression analysis was used.

Frequently asked questions about writing an APA methods section

What should I include in an APA methods section?

In your APA methods section, you should report detailed information on the participants, materials, and procedures used.

  • Describe all relevant participant or subject characteristics, the sampling procedures used and the sample size and power.
  • Define all primary and secondary measures and discuss the quality of measurements.
  • Specify the data collection methods, the research design and data analysis strategy, including any steps taken to transform the data and statistical analyses.
What tense should I write the methods section in?

You should report methods using the past tense, even if you haven’t completed your study at the time of writing. That’s because the methods section is intended to describe completed actions or research.

Where does the methodology section go in a research paper?

In a scientific paper, the methodology always comes after the introduction and before the results, discussion and conclusion. The same basic structure also applies to a thesis, dissertation, or research proposal.

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

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Pritha Bhandari

Pritha has an academic background in English, psychology and cognitive neuroscience. As an interdisciplinary researcher, she enjoys writing articles explaining tricky research concepts for students and academics.

1 comment

Pritha Bhandari
Pritha Bhandari (Scribbr Team)
February 5, 2021 at 8:56 PM

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