{"id":819,"date":"2026-06-10T04:41:39","date_gmt":"2026-06-10T04:41:39","guid":{"rendered":"https:\/\/www.editage.com\/blog\/?p=819"},"modified":"2026-06-29T03:41:30","modified_gmt":"2026-06-29T03:41:30","slug":"within-subjects-design","status":"publish","type":"post","link":"https:\/\/www.editage.com\/blog\/within-subjects-design\/","title":{"rendered":"Using a Within-Subjects Design in Research: Steps, Tips, Examples"},"content":{"rendered":"\n<h2><\/h2>\n\n\n\n<p>Contents<\/p>\n\n\n\n<p><a href=\"#_Toc231978576\"><\/a><\/p>\n\n\n\n<ul><li><a href=\"#_Toc231978577\">Introduction<\/a><\/li><li><a href=\"#_Toc231978578\">Glossary of Key Terms<\/a><\/li><li><a href=\"#_Toc231978579\">What Is a Within-Subjects Design?<\/a><\/li><li><a href=\"#_Toc231978580\">How a Within-Subjects Design Works<\/a><\/li><li><a href=\"#_Toc231978581\">Examples of Within-Subjects Designs<\/a><\/li><li><a href=\"#_Toc231978582\">Within-Subjects vs. Between-Subjects Design<\/a><\/li><li><a href=\"#_Toc231978583\">Benefits of a Within-Subjects Design<\/a><\/li><li><a href=\"#_Toc231978584\">Problems with a Within-Subjects Design<\/a><\/li><li><a href=\"#_Toc231978585\">Combining Within- and Between-Subjects Designs<\/a><\/li><li><a href=\"#_Toc231978586\">Frequently Asked Questions<\/a><\/li><\/ul>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Introduction\" >Introduction<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Glossary_of_Key_Terms\" >Glossary of Key Terms<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#What_Is_a_Within-Subjects_Design\" >What Is a Within-Subjects Design?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#How_a_Within-Subjects_Design_Works\" >How a Within-Subjects Design Works<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Comparing_different_treatments\" >Comparing different treatments<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Comparing_measurements_over_time\" >Comparing measurements over time<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Counterbalancing_vs_randomizing_condition_order\" >Counterbalancing vs. randomizing condition order<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Examples_of_Within-Subjects_Designs\" >Examples of Within-Subjects Designs<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Example_from_the_social_sciences_message_styles_and_generosity\" >Example from the social sciences: message styles and generosity<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Example_from_the_social_sciences_tracking_attitudes_over_time\" >Example from the social sciences: tracking attitudes over time<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Example_from_the_biomedical_sciences_a_crossover_trial\" >Example from the biomedical sciences: a crossover trial<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Within-Subjects_vs_Between-Subjects_Design\" >Within-Subjects vs. Between-Subjects Design<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Worked_contrast\" >Worked contrast:<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Benefits_of_a_Within-Subjects_Design\" >Benefits of a Within-Subjects Design<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Problems_with_a_Within-Subjects_Design\" >Problems with a Within-Subjects Design<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Time-related_effects\" >Time-related effects<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Carryover_effects\" >Carryover effects<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#How_to_minimize_these_threats\" >How to minimize these threats<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Combining_Within-_and_Between-Subjects_Designs\" >Combining Within- and Between-Subjects Designs<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Example\" >Example:<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#What_is_the_difference_between_a_within-subjects_design_and_a_between-subjects_design\" >What is the difference between a within-subjects design and a between-subjects design?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#Why_do_within-subjects_designs_need_fewer_participants_than_between-subjects_designs\" >Why do within-subjects designs need fewer participants than between-subjects designs?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-24\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#What_is_a_2%C3%972_within-subjects_design\" >What is a 2&#215;2 within-subjects design?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-25\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#How_do_you_control_order_effects_in_a_within-subjects_design\" >How do you control order effects in a within-subjects design?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-26\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#When_should_a_within-subjects_design_not_be_used\" >When should a within-subjects design not be used?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Introduction\"><\/span><a id=\"_Toc231978577\">Introduction<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In an experiment, a different treatment or manipulation of the independent variable is applied in each condition to test for a cause-and-effect relationship with a dependent variable. In a <strong>within-subjects design<\/strong> (also called a within-groups, repeated measures, or dependent-groups design), every participant takes part in every condition. Researchers compare related measurements taken from the same people across conditions or across time.<\/p>\n\n\n\n<p>It is the opposite of a between-subjects design, in which each participant experiences only one condition. The word <em>within<\/em> signals that conditions are compared within the same group or individual, whereas <em>between<\/em> signals comparison between separate groups. Because the same people appear in every condition, each participant effectively serves as their own control, and all longitudinal studies, which track the same individuals over time, use a within-subjects design.<\/p>\n\n\n\n<p>This guide defines the design, illustrates it with examples from the social sciences and biomedical sciences, explains counterbalancing, and weighs its considerable statistical advantages against its threats to <a href=\"https:\/\/www.editage.com\/blog\/internal-validity-external-validity-definition-differences-examples\/\">internal validity<\/a>.<\/p>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Glossary_of_Key_Terms\"><\/span><a id=\"_Toc231978578\">Glossary of Key Terms<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Term<\/strong><\/td><td><strong>Definition<\/strong><\/td><\/tr><tr><td>Within-subjects design<\/td><td>An experimental design in which all participants are exposed to every condition, and related measures from the same people are compared across conditions.<\/td><\/tr><tr><td>Repeated measures<\/td><td>Multiple measurements of the dependent variable taken from the same participant, across conditions or time points.<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/insights\/independent-vs-dependent-variables-key-differences-with-examples\">Independent variable<\/a> (IV)<\/td><td>The variable that is manipulated (e.g., message style, drug dose) or that defines the comparison (e.g., time).<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/insights\/independent-vs-dependent-variables-key-differences-with-examples\">Dependent variable<\/a> (DV)<\/td><td>The outcome that is measured (e.g., willingness to donate, blood pressure, test scores).<\/td><\/tr><tr><td>Own control (baseline)<\/td><td>Each participant\u2019s scores in one condition (often a <a href=\"https:\/\/www.editage.com\/blog\/pretest-posttest-before-after-design\/\" target=\"_blank\" rel=\"noreferrer noopener\">pretest<\/a>) act as the comparison point for their scores in other conditions; no separate control group is needed.<\/td><\/tr><tr><td>Carryover effects<\/td><td>Effects of an earlier condition that spill over and alter responses in a later condition.<\/td><\/tr><tr><td>Practice (learning) effect<\/td><td>Improvement in later conditions caused by familiarity gained in earlier conditions.<\/td><\/tr><tr><td>Order effect<\/td><td>A change in outcomes caused by a condition\u2019s position in the sequence (e.g., poorer attention in the final condition due to fatigue or boredom).<\/td><\/tr><tr><td>Sequence effect<\/td><td>An interaction between conditions based on their order (e.g., rating later items by comparing them with earlier ones).<\/td><\/tr><tr><td>Counterbalancing<\/td><td>Presenting conditions in a limited set of fixed sequences distributed evenly across participants to balance out order effects.<\/td><\/tr><tr><td>Randomization (of order)<\/td><td>Presenting conditions in randomly generated sequences that vary across participants.<\/td><\/tr><tr><td>Washout period<\/td><td>In crossover trials, a treatment-free interval between conditions that lets the first treatment\u2019s effects dissipate.<\/td><\/tr><tr><td>Attrition<\/td><td>Loss of participants over the course of a study, which can bias longitudinal results.<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/insights\/importance-of-statistical-power-in-research-design\">Statistical power<\/a><\/td><td>The probability of detecting a true effect; within-subjects designs gain power by removing between-person variability.<\/td><\/tr><tr><td><a href=\"https:\/\/researcher.life\/blog\/article\/what-is-a-longitudinal-study-definition-advantages-and-examples\/\">Longitudinal study<\/a><\/td><td>A study that repeatedly measures the same individuals over time, treating time as an independent variable.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"What_Is_a_Within-Subjects_Design\"><\/span><a id=\"_Toc231978579\">What Is a Within-Subjects Design?<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In a within-subjects design, the entire sample is exposed to all treatments or conditions, and the analysis compares each person\u2019s responses across those conditions. The defining features are:<\/p>\n\n\n\n<ul><li><strong>Every participant, every condition. <\/strong>No one is left out of any level of the independent variable.<\/li><li><strong>Related (dependent) measurements. <\/strong>The scores being compared come from the same individuals, so they are statistically paired.<\/li><li><strong>No separate <\/strong><a href=\"https:\/\/www.editage.com\/blog\/control-group\/\"><strong>control group.<\/strong><\/a><strong> <\/strong>Participants are compared with themselves; a pretest functions like a control condition taken before any treatment, and a posttest is taken afterward.<\/li><li><strong>Two typical goals. <\/strong>Measuring change produced by different treatments (e.g., five message styles) or change over time (e.g., attitudes tracked across a year), for outcomes such as attitudes, learning, or performance.<\/li><\/ul>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"How_a_Within-Subjects_Design_Works\"><\/span><a id=\"_Toc231978580\">How a Within-Subjects Design Works<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Comparing_different_treatments\"><\/span>Comparing different treatments<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>When the conditions are different treatments, every participant completes all of them, usually in a single session or a short series of sessions, and the order of conditions is varied across participants. Filler tasks or unrelated questions are often added so participants cannot guess the aim of the study.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Comparing_measurements_over_time\"><\/span>Comparing measurements over time<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>In longitudinal research, time itself is the independent variable. Because researchers cannot manipulate or prevent the passage of time, longitudinal studies usually examine correlations between time and the outcome rather than strict causal effects. For example, a social researcher might survey the same panel of respondents every two to three months, asking them to rate their fear of infection during a pandemic on a 7-point <a href=\"https:\/\/researcher.life\/blog\/article\/what-is-a-likert-scale-definition-types-and-examples\/\">Likert scale<\/a>, and then track how those ratings shift over the months.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Counterbalancing_vs_randomizing_condition_order\"><\/span>Counterbalancing vs. randomizing condition order<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Whenever multiple treatments are compared within subjects, the order of conditions should be randomized or counterbalanced so that earlier treatments do not systematically spill over onto later ones.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Approach<\/strong><\/td><td><strong>How it works<\/strong><\/td><td><strong>Key feature<\/strong><\/td><\/tr><tr><td>Counterbalancing<\/td><td>The researcher selects a limited number of fixed sequences (e.g., A-B-C-D-E, B-E-A-C-D, D-A-B-E-C) and assigns an equal share of participants to each sequence.<\/td><td>Controlled: ideally each treatment appears equally often in each serial position, balancing order effects across the sample.<\/td><\/tr><tr><td>Randomization<\/td><td>A computer generates the order of conditions afresh for each participant, so any possible sequence may occur.<\/td><td>Uncontrolled frequencies: the researcher cannot guarantee how often each sequence appears across the group.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Counterbalancing is often more convenient because the researcher knows exactly which sequences occur and how often, whereas full randomization leaves sequence frequencies to chance.<\/p>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Examples_of_Within-Subjects_Designs\"><\/span><a id=\"_Toc231978581\">Examples of Within-Subjects Designs<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Example_from_the_social_sciences_message_styles_and_generosity\"><\/span>Example from the social sciences: message styles and generosity<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Suppose you are studying how different messaging styles (independent variable) affect generosity (dependent variable). Every participant reads five short stories about climate change, each written in a different tone and style. After each story, participants report how they feel and how willing they are to donate to a related cause; unrelated filler questions disguise the purpose of the study. You then compare willingness to donate across the five conditions within each participant, after counterbalancing or randomizing the order of the stories.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Example_from_the_social_sciences_tracking_attitudes_over_time\"><\/span>Example from the social sciences: tracking attitudes over time<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A panel study recruits a large sample early in a public-health crisis and re-surveys the same people every few months. Because each respondent provides repeated ratings, changes in perception can be assessed within individuals over time, which is something no single-snapshot between-subjects survey could reveal.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Example_from_the_biomedical_sciences_a_crossover_trial\"><\/span>Example from the biomedical sciences: a crossover trial<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The classic biomedical application of a within-subjects design is the crossover trial. To compare two inhalers for asthma:<\/p>\n\n\n\n<ul><li>Each patient uses Inhaler A for four weeks, completes a washout period during which the first drug\u2019s effects wear off, and then uses Inhaler B for four weeks (or in the reverse order).<\/li><li>Patients are randomized to the A-then-B or B-then-A sequence, which counterbalances order.<\/li><li>Lung function is measured at the end of each treatment period and compared within each patient.<\/li><\/ul>\n\n\n\n<p>Because each patient\u2019s physiology, age, disease severity, and lifestyle stay constant across both treatments, the comparison is far less noisy than a parallel-group trial, and far fewer patients are needed.<\/p>\n\n\n\n<p><strong>Note:<\/strong> Crossover trials are only appropriate for stable, chronic conditions and reversible treatments; they are unsuitable when a treatment cures the condition or when carryover cannot be eliminated by a washout.<\/p>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Within-Subjects_vs_Between-Subjects_Design\"><\/span><a id=\"_Toc231978582\">Within-Subjects vs. Between-Subjects Design<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In a <a href=\"https:\/\/www.editage.com\/blog\/between-subjects-design\/\">between-subjects design<\/a>, each participant experiences only one condition, and separate groups, typically one or more experimental groups plus a control group, are compared with each other. The table below contrasts the two designs.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Feature<\/strong><\/td><td><strong>Within-subjects design<\/strong><\/td><td><strong>Between-subjects design<\/strong><\/td><\/tr><tr><td>Conditions per participant<\/td><td>All<\/td><td>One<\/td><\/tr><tr><td>Other names<\/td><td>Repeated measures, dependent groups<\/td><td>Independent measures, between-groups<\/td><\/tr><tr><td>Control<\/td><td>Participants serve as their own control (baseline\/pretest)<\/td><td>Separate control group (no treatment, usual care, or placebo)<\/td><\/tr><tr><td>Sample size needed<\/td><td>Smaller; each person yields a data point for every condition<\/td><td>Often double or more for the same statistical power<\/td><\/tr><tr><td>Time per participant<\/td><td>Longer (multiple conditions or repeated visits)<\/td><td>Shorter (a single session)<\/td><\/tr><tr><td>Individual differences<\/td><td>Controlled; the same people appear in every condition<\/td><td>A threat; groups may differ in ability, motivation, or health<\/td><\/tr><tr><td>Main validity threats<\/td><td>Carryover, practice, order, fatigue, and time-related effects<\/td><td>Group non-equivalence and selection effects<\/td><\/tr><tr><td>Typical analyses<\/td><td><a href=\"https:\/\/www.editage.com\/insights\/what-biomedical-researchers-need-to-know-about-t-tests\" target=\"_blank\" rel=\"noreferrer noopener\">Paired t test<\/a>, <a href=\"https:\/\/www.editage.com\/blog\/anova-types-uses-assumptions-a-quick-guide-for-biomedical-researchers\/\">repeated measures ANOVA<\/a><\/td><td><a href=\"https:\/\/www.editage.com\/insights\/what-biomedical-researchers-need-to-know-about-t-tests\" target=\"_blank\" rel=\"noreferrer noopener\">Independent-samples t test<\/a>, <a href=\"https:\/\/www.editage.com\/blog\/anova-types-uses-assumptions-a-quick-guide-for-biomedical-researchers\/\">one-way ANOVA<\/a><\/td><\/tr><tr><td>Biomedical archetype<\/td><td>Crossover trial<\/td><td>Parallel-group randomized controlled trial<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h4><span class=\"ez-toc-section\" id=\"Worked_contrast\"><\/span>Worked contrast:<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>To test whether learning environment (on campus vs. online) affects test scores, a between-subjects design would randomize students to take a course either on campus or online and compare the groups\u2019 test scores. A within-subjects design would have every student take half the course on campus and half online, with the order randomized across students, and would compare each student\u2019s scores under the two formats.<\/p>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Benefits_of_a_Within-Subjects_Design\"><\/span><a id=\"_Toc231978583\">Benefits of a Within-Subjects Design<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Within-subjects designs can detect causal or correlational relationships with relatively small samples, for three connected reasons:<\/p>\n\n\n\n<ul><li><strong>Smaller samples and lower cost. <\/strong>Each participant supplies repeated measures, so far fewer people are needed. Recruitment is easier and the study is more cost-effective per data point.<\/li><li><strong>Individual differences are removed from the comparison. <\/strong>In a between-subjects study, characteristics such as intelligence, memory capacity, or disease severity vary between the groups and can masquerade as treatment effects. In a within-subjects study, the same individuals appear in every condition, so those characteristics are held constant.<\/li><li><strong>Greater <\/strong><a href=\"https:\/\/www.editage.com\/insights\/importance-of-statistical-power-in-research-design\"><strong>statistical power.<\/strong><\/a><strong> <\/strong>Removing between-person variation shrinks the error term. A between-subjects design typically needs about twice as many participants (or more) to achieve the power of an equivalent within-subjects design. Simulation research on mediation analysis likewise finds that within-subjects designs need roughly half the sample to detect indirect effects of the same size, though the exact advantage depends on effect sizes and the <a href=\"https:\/\/www.editage.com\/insights\/5-things-biomedical-researchers-need-to-know-about-correlation-analysis\">correlation<\/a> between repeated measures.<\/li><\/ul>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Problems_with_a_Within-Subjects_Design\"><\/span><a id=\"_Toc231978584\">Problems with a Within-Subjects Design<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The biggest drawbacks are threats to internal validity. Repeated testing, sometimes over long periods, opens the door to alternative explanations of the results.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Time-related_effects\"><\/span>Time-related effects<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Several threats apply specifically to designs that test the same people across time:<\/p>\n\n\n\n<ul><li><strong>History: <\/strong>an unrelated external event (e.g., a lockdown, a policy change, a news story) occurs between measurements and influences the outcome.<\/li><li><strong>Maturation: <\/strong>natural physical or psychological change, such as growth, aging, healing, or developing skills, produces the observed differences rather than the treatment.<\/li><li><strong>Subject attrition: <\/strong>participants drop out at each successive wave, leaving a biased final sample in which only the most motivated (or healthiest) individuals remain.<\/li><\/ul>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Carryover_effects\"><\/span>Carryover effects<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Carryover effects are a broad family of threats that arise when an earlier condition alters responses in a later one:<\/p>\n\n\n\n<ul><li><strong>Practice (learning) effects: <\/strong>familiarity with the task gained in early conditions improves performance in later conditions.<\/li><li><strong>Order effects: <\/strong>the serial position of a condition changes outcomes, for instance, participants grow bored or fatigued and pay less attention in the final condition.<\/li><li><strong>Sequence effects: <\/strong>conditions interact based on their order, as when raters judge later advertisements by comparing them with the ones they saw earlier.<\/li><li><strong>Participant fatigue<\/strong> deserves special mention: people who complete several treatments in a row can become tired, bored, or unmotivated, degrading data quality in the later conditions.<\/li><\/ul>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"How_to_minimize_these_threats\"><\/span>How to minimize these threats<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul><li>Randomize or counterbalance the order of conditions across participants.<\/li><li>Insert washout periods (in drug studies) or breaks and filler tasks between conditions.<\/li><li>Use parallel forms of tests so that the identical items are never repeated.<\/li><li>Keep sessions short and offer incentives to limit fatigue and attrition.<\/li><li>Track and report dropout, and compare completers with non-completers to gauge attrition bias.<\/li><\/ul>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Combining_Within-_and_Between-Subjects_Designs\"><\/span><a id=\"_Toc231978585\">Combining Within- and Between-Subjects Designs<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>With two or more independent variables, the two approaches can be combined in a factorial design, in which every level of each independent variable is crossed with every level of the others. In a mixed factorial design, one variable is manipulated between subjects and another within subjects.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Example\"><\/span>Example:<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>An education researcher investigates whether teaching method affects second-language learning in 8th-grade students. Students are randomly assigned to standard or experimental teaching methods (the between-subjects factor), and every student is tested before, midway through, and after the course (the within-subjects factor). Scores are then analyzed for differences across time, between groups, and for their interaction. Longitudinal studies of this kind can be genuinely experimental when the researcher directly manipulates one independent variable and controls assignment to its conditions.<\/p>\n\n\n\n<p>When choosing between the two designs, methodologists advise weighing three factors together: validity (within-subjects designs face carryover, participant awareness, and measurement artifacts), causality (between-subjects designs require no-confounder assumptions, while within-subjects designs require the assumption of no carryover), and statistical power (which favors within-subjects designs). Higher power alone is not a sufficient reason to choose a within-subjects design.<\/p>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span><a id=\"_Toc231978586\">Frequently Asked Questions<\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"What_is_the_difference_between_a_within-subjects_design_and_a_between-subjects_design\"><\/span>What is the difference between a within-subjects design and a between-subjects design?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>In a within-subjects design, each participant experiences all conditions, and the same people are tested repeatedly so conditions can be compared within individuals. In a between-subjects design, every participant experiences only one condition, and outcomes are compared between separate groups. \u201cWithin\u201d means comparing conditions within the same group; \u201cbetween\u201d means comparing conditions between groups.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"Why_do_within-subjects_designs_need_fewer_participants_than_between-subjects_designs\"><\/span>Why do within-subjects designs need fewer participants than between-subjects designs?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Because every participant contributes a data point to every condition, and because comparing people with themselves removes between-person variability from the error term. The result is higher statistical power per participant: a between-subjects design typically needs roughly twice as many people to detect the same effect, and simulations of mediation analysis show a similar two-to-one sample-size advantage for within-subjects designs.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"What_is_a_2%C3%972_within-subjects_design\"><\/span>What is a 2&#215;2 within-subjects design?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A 2&#215;2 within-subjects design is a factorial design with two independent variables, each having two levels, in which every participant experiences all four combinations of conditions. It lets researchers estimate the effect of each variable and their interaction on a single dependent variable using one sample of participants.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"How_do_you_control_order_effects_in_a_within-subjects_design\"><\/span>How do you control order effects in a within-subjects design?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The two main tools are counterbalancing, assigning equal portions of the sample to a limited set of fixed condition sequences so each treatment appears equally often in each position, and randomization, generating a fresh random order for each participant. Washout periods, breaks, filler tasks, and parallel test forms further reduce carryover, practice, and fatigue effects.<\/p>\n\n\n\n<h3><span class=\"ez-toc-section\" id=\"When_should_a_within-subjects_design_not_be_used\"><\/span>When should a within-subjects design not be used?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Avoid a within-subjects design when practice or carryover effects cannot be eliminated, when you need to observe treatment effects under minimum practice (repeated testing inevitably gives later conditions extra practice), when a treatment is irreversible or curative (e.g., surgery), when contrasting conditions would reveal the hypothesis to participants, or when long repeated testing would cause heavy fatigue or attrition. In those situations, a between-subjects design protects internal validity better despite needing a larger sample.<\/p>\n","protected":false},"excerpt":{"rendered":"Contents Introduction Glossary of Key Terms What Is a Within-Subjects Design? How a Within-Subjects Design Works Examples of Within-Subjects Designs Within-Subjects vs. Between-Subjects Design Benefits of a Within-Subjects Design Problems with a Within-Subjects Design Combining Within- and Between-Subjects Designs Frequently Asked Questions Introduction In an experiment, a different treatment or manipulation of the independent variable [&hellip;]","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_ayudawp_aiss_exclude":false,"_ayudawp_aiss_summary":"In a within-subjects design (also called a within-groups, repeated measures, or dependent-groups design), every participant takes part in every condition. When choosing between the two designs, methodologists advise weighing three factors together: validity (within-subjects designs face carryover, participant awareness, and measurement artifacts), causality (between-subjects designs require no-confounder assumptions, while within-subjects designs require the assumption of no carryover), and statistical power (which favors within-subjects designs). In a between-subjects design, every participant experiences only one condition, and outcomes are compared between separate groups. \u201cWithin\u201d means comparing conditions within the same group; \u201cbetween\u201d means comparing conditions between groups.","_ayudawp_aiss_summary_provider":"extractive","_ayudawp_aiss_summary_hash":"efd4a609ebe55e33fc4e577828b4c1708f967a5f"},"categories":[14],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Within-Subjects Design in Research: Steps, Tips, Examples, Pros &amp; Cons<\/title>\n<meta name=\"description\" content=\"Learn what is a within-subjects design, how to use it, repeated-measures analysis, carryover effects, washout period, and pros and cons.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Within-Subjects Design in Research: Steps, Tips, Examples, Pros &amp; Cons\" \/>\n<meta property=\"og:description\" content=\"Learn what is a within-subjects design, how to use it, repeated-measures analysis, carryover effects, washout period, and pros and cons.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.editage.com\/blog\/within-subjects-design\/\" \/>\n<meta property=\"og:site_name\" content=\"Educational Articles For Researchers, Students And Authors - Editage Blog\" \/>\n<meta property=\"article:published_time\" content=\"2026-06-10T04:41:39+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-06-29T03:41:30+00:00\" \/>\n<meta name=\"author\" content=\"Marisha Rodrigues\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Marisha Rodrigues\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"11 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.editage.com\/blog\/within-subjects-design\/\"},\"author\":{\"name\":\"Marisha Rodrigues\",\"@id\":\"https:\/\/www.editage.com\/blog\/#\/schema\/person\/60d7626072744221b2260692486b6ff1\"},\"headline\":\"Using a Within-Subjects Design in Research: Steps, Tips, Examples\",\"datePublished\":\"2026-06-10T04:41:39+00:00\",\"dateModified\":\"2026-06-29T03:41:30+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.editage.com\/blog\/within-subjects-design\/\"},\"wordCount\":2423,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.editage.com\/blog\/#organization\"},\"articleSection\":[\"Research Tips\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.editage.com\/blog\/within-subjects-design\/\",\"url\":\"https:\/\/www.editage.com\/blog\/within-subjects-design\/\",\"name\":\"Within-Subjects Design in Research: Steps, Tips, Examples, Pros & Cons\",\"isPartOf\":{\"@id\":\"https:\/\/www.editage.com\/blog\/#website\"},\"datePublished\":\"2026-06-10T04:41:39+00:00\",\"dateModified\":\"2026-06-29T03:41:30+00:00\",\"description\":\"Learn what is a within-subjects design, how to use it, repeated-measures analysis, carryover effects, washout period, and pros and cons.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.editage.com\/blog\/within-subjects-design\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.editage.com\/blog\/within-subjects-design\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.editage.com\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Using a Within-Subjects Design in Research: Steps, Tips, Examples\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.editage.com\/blog\/#website\",\"url\":\"https:\/\/www.editage.com\/blog\/\",\"name\":\"Educational Articles For Researchers, Students And Authors - Editage Blog\",\"description\":\"Get insightful educational articles from the world of academia for researchers, students and authors. 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