{"id":4230,"date":"2023-07-05T04:57:42","date_gmt":"2023-07-05T04:57:42","guid":{"rendered":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\/"},"modified":"2025-01-15T06:21:05","modified_gmt":"2025-01-15T06:21:05","slug":"all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes","status":"publish","type":"post","link":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes","title":{"rendered":"All you need to know about repeated measures analysis in 5 minutes"},"content":{"rendered":"<p style=\"margin:0cm 0cm 8pt\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\">Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results? <\/span><\/span><\/span><\/p>\n<p style=\"margin:0cm 0cm 8pt\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\">Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time <i>while taking into account the correlated nature of the measurements<\/i>. This method is especially useful when we have multiple observations from the same subjects, which is quite common in biomedical research.<\/span><\/span><\/span><\/p>\n<p style=\"margin:0cm 0cm 8pt\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\">Let\u2019s say we have a cohort of individuals with diabetes, and we want to study the effect of a new medication on their blood glucose levels over time. We measure their blood glucose levels before starting the medication (baseline), and then at regular intervals (e.g., weekly) for a duration of three months.<\/span><\/span><\/span><\/p>\n<p style=\"margin:0cm 0cm 8pt\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\">Using repeated measures analysis, we can analyze the changes in blood glucose levels within each individual over time, while accounting for the correlation between the measurements. This analysis allows us to determine if the medication has a significant effect on reducing blood glucose levels compared to the baseline, considering the within-subject variability and any potential confounding factors. Instead of treating each measurement independently, repeated measures analysis considers the interdependency of the measurements, providing us with more accurate and powerful results.\u00a0 Some participants may be genetically predisposed to high blood glucose levels, while others may have more physically active lifestyles. In a repeated-measures analysis, we can see whether the medication changes blood glucose levels for these participants, considering <i>what their previous levels were. <\/i>\u00a0<\/span><\/span><\/span><\/p>\n<h2 style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><b>Benefits of Repeated Measures Analysis<\/b><\/span><\/span><\/span><\/h2>\n<ul>\n<li>\n<p style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Increased Precision<\/i>: By accounting for the correlation between measurements, repeated measures analysis can improve the efficiency and precision of our <a href=\"https:\/\/www.editage.com\/insights\/statistical-reporting-doesnt-have-to-be-scary-tips-for-the-statistically-challenged-researcher?refer-type=article\" style=\"color:#0563c1; text-decoration:underline\">statistical tests<\/a>.<\/span><\/span><\/span><\/p>\n<\/li>\n<li>\n<p style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Reduced Variability<\/i>: Accounting for within-subject variability can help us tease out the true changes over time, as it minimizes the impact of individual differences between participants. This is particularly valuable when we\u2019re studying something that\u2019s relatively subjective, such as pain perception or self-efficacy.<\/span><\/span><\/span><\/p>\n<\/li>\n<li>\n<p style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Enhanced Control<\/i>: Repeated measures analysis allows us to control for confounding factors that remain constant within subjects, such as genetic predispositions or socioeconomic status. By doing so, we can gain a clearer understanding of the specific effects we\u2019re interested in.<\/span><\/span><\/span><\/p>\n<\/li>\n<\/ul>\n<h2 style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><b>Making the Most of Repeated Measures Analysis<\/b><\/span><\/span><\/span><\/h2>\n<p style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\">Here are some essential steps you must follow, to make the most of your repeated-measures analysis:<\/span><\/span><\/span><\/p>\n<ul>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Data Preparation<\/i>: As with any statistical analysis, good data preparation is crucial. Make sure you have a well-structured dataset, with each row representing a unique subject and columns representing different time points or conditions. Also, you\u2019ll need to take measures to deal with <a href=\"https:\/\/www.editage.com\/insights\/statistical-solutions-to-overcome-missing-data-in-clinical-trials-and-observational-studies?refer=insights-search-posts\" style=\"color:#0563c1; text-decoration:underline\">missing data<\/a>, outliers, and potential sources of bias.<\/span><\/span><\/span><\/li>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Choosing the Correct Analysis<\/i>: Repeated measures analysis offers various methods, depending on the nature of your data and research question. Some commonly used techniques include repeated measures <a href=\"https:\/\/www.editage.com\/blog\/anova-types-uses-assumptions-a-quick-guide-for-biomedical-researchers\/\" style=\"color:#0563c1; text-decoration:underline\">ANOVA<\/a>, linear mixed-effects models, and generalized estimating equations (GEE). Consult with a statistician to determine the most appropriate method for your study.<\/span><\/span><\/span><\/li>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Assumptions and Model Checking<\/i>: Repeated measures analysis has certain <a href=\"https:\/\/www.editage.com\/insights\/4-important-precautions-for-biomedical-researchers-during-statistical-analysis?refer-type=infographics\" style=\"color:#0563c1; text-decoration:underline\">assumptions<\/a> that need to be met. These may include sphericity (equal variances between time points), linearity, and normality of residuals. Always check these assumptions and explore diagnostic plots to ensure the validity of your results.<\/span><\/span><\/span><\/li>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Interpretation<\/i>: Once you\u2019ve obtained your results, it\u2019s time to interpret them in the context of your research question. Pay attention to effect sizes, confidence intervals, and p-values, but remember that statistical significance is not the only criterion for <a href=\"https:\/\/www.editage.com\/insights\/5-statistical-terms-that-biomedical-researchers-need-to-use-carefully?refer-type=article\" style=\"color:#0563c1; text-decoration:underline\">drawing conclusions<\/a>. Consider the clinical or biological relevance of your findings and their implications for future research.<\/span><\/span><\/span><\/li>\n<\/ul>\n<h2 style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><b>When You Should Avoid Repeated-Measures Analysis<\/b><\/span><\/span><\/span><\/h2>\n<p style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\">Although repeated-measures analysis can be very useful, it\u2019s not <i>always<\/i> the best solution to your statistical problems. You\u2019ll need to exercise caution or avoid using repeated measures analysis in the following scenarios:<\/span><\/span><\/span><\/p>\n<ul>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Independence of Measurements<\/i>: Repeated measures analysis assumes that measurements within the same subject are correlated. If the measurements are truly independent, a different analysis approach, like the independent samples <a href=\"https:\/\/www.editage.com\/insights\/whats-the-best-way-to-check-for-differences-between-groups-t-test-chi-square-test-or-anova-a-quick-and-simple-guide?refer-type=article\" style=\"color:#0563c1; text-decoration:underline\">t test<\/a>, would be more appropriate.<\/span><\/span><\/span><\/li>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Violation of Assumptions<\/i>: Repeated measures analysis has certain assumptions, including sphericity (equal variances between time points) and linearity. If these assumptions are violated, alternative methods, such as robust regression or non-parametric tests, may be more suitable.<\/span><\/span><\/span><\/li>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Incomplete or Uneven Data<\/i>: Repeated measures analysis requires a complete set of measurements for each subject across all time points. If you have a lot of missing data or uneven measurement intervals, it may complicate the analysis or lead to biased results. In such cases, <a href=\"https:\/\/www.editage.com\/insights\/statistical-solutions-to-overcome-missing-data-in-clinical-trials-and-observational-studies?refer=insights-search-posts\" style=\"color:#0563c1; text-decoration:underline\">imputation techniques<\/a> or alternative analytical methods should be considered.<\/span><\/span><\/span><\/li>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Different Sample Sizes<\/i>: If the number of subjects or measurements differs substantially between time points or conditions, it can introduce biases in the analysis. So when your <a href=\"https:\/\/www.editage.com\/insights\/importance-of-statistical-power-in-research-design?refer=insights-search-posts\" style=\"color:#0563c1; text-decoration:underline\">sample size<\/a> varies a lot between measurements, specialized methods like weighted or mixed-effects models may be more appropriate.<\/span><\/span><\/span><\/li>\n<li style=\"margin: 0cm 0cm 8pt;\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Violation of the Correlation Structure<\/i>: Repeated measures analysis assumes a specific correlation structure, such as compound symmetry or autoregressive correlation (i.e., the variances of the differences between all possible pairs of measurements are equal, and the correlations between the measurements are the same). If the correlation pattern in the data deviates from these assumptions, it may impact the validity of the analysis. Exploratory analyses or alternative models that account for specific correlation structures may be more suitable.<\/span><\/span><\/span><\/li>\n<\/ul>\n<p style=\"margin:0cm 0cm 8pt\"><span style=\"font-size:11pt\"><span style=\"line-height:107%\"><span style=\"font-family:Calibri,sans-serif\"><i>Do you want to unlock the power of repeated-measures analysis and other valuable statistical techniques in your research? Consult an expert biostatistician under Editage\u2019s <\/i><a href=\"https:\/\/www.editage.com\/services\/publishing-services-packs\/statistical-analysis\" style=\"color:#0563c1; text-decoration:underline\"><i>Statistical Analysis &amp; Review Services<\/i><\/a><span class=\"MsoHyperlink\" style=\"color:#0563c1\"><span style=\"text-decoration:underline\">.<\/span><\/span><\/span><\/span><\/span><\/p>\n<p style=\"margin:0cm 0cm 8pt\">\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results? Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time while taking into account the correlated nature of the measurements. This method [&hellip;]<\/p>\n","protected":false},"author":15,"featured_media":33313,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[2420],"tags":[2622,1319,366],"new_categories":[],"new_tags":[],"series":[],"class_list":["post-4230","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-analysis","tag-analysisofdata","tag-statistical-analysis","tag-statistical-reporting"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>All you need to know about repeated measures analysis in 5 minutes | Editage Insights<\/title>\n<meta name=\"description\" content=\"Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results?\u00a0Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time while taking into account the correlated nature of the measurements. Read this article to find out the details.\" \/>\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\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"All you need to know about repeated measures analysis in 5 minutes | Editage Insights\" \/>\n<meta property=\"og:description\" content=\"Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results?\u00a0Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time while taking into account the correlated nature of the measurements. Read this article to find out the details.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\" \/>\n<meta property=\"og:site_name\" content=\"Editage Insights\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/Editage\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-05T04:57:42+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-01-15T06:21:05+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2023\/07\/pexels-fauxels-3183131-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"656\" \/>\n\t<meta property=\"og:image:height\" content=\"336\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Marisha Fonseca\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@Editage\" \/>\n<meta name=\"twitter:site\" content=\"@Editage\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Marisha Fonseca\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\"},\"author\":{\"name\":\"Marisha Fonseca\",\"@id\":\"https:\/\/www.editage.com\/insights\/#\/schema\/person\/d7c4142919456ea4250396c49fe1f777\"},\"headline\":\"All you need to know about repeated measures analysis in 5 minutes\",\"datePublished\":\"2023-07-05T04:57:42+00:00\",\"dateModified\":\"2025-01-15T06:21:05+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\"},\"wordCount\":917,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.editage.com\/insights\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp\",\"keywords\":[\"Analysis of Data\",\"statistical analysis\",\"statistical reporting\"],\"articleSection\":[\"Data Analysis\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\",\"url\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\",\"name\":\"All you need to know about repeated measures analysis in 5 minutes | Editage Insights\",\"isPartOf\":{\"@id\":\"https:\/\/www.editage.com\/insights\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp\",\"datePublished\":\"2023-07-05T04:57:42+00:00\",\"dateModified\":\"2025-01-15T06:21:05+00:00\",\"description\":\"Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results?\u00a0Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time while taking into account the correlated nature of the measurements. Read this article to find out the details.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage\",\"url\":\"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp\",\"contentUrl\":\"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp\",\"width\":656,\"height\":336},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.editage.com\/insights\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"All you need to know about repeated measures analysis in 5 minutes\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.editage.com\/insights\/#website\",\"url\":\"https:\/\/www.editage.com\/insights\/\",\"name\":\"Editage Insights\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/www.editage.com\/insights\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.editage.com\/insights\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/www.editage.com\/insights\/#organization\",\"name\":\"Editage Insights\",\"url\":\"https:\/\/www.editage.com\/insights\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.editage.com\/insights\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2024\/09\/editage-insights-logo-1-scaled.webp\",\"contentUrl\":\"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2024\/09\/editage-insights-logo-1-scaled.webp\",\"width\":2560,\"height\":324,\"caption\":\"Editage Insights\"},\"image\":{\"@id\":\"https:\/\/www.editage.com\/insights\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/Editage\",\"https:\/\/x.com\/Editage\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.editage.com\/insights\/#\/schema\/person\/d7c4142919456ea4250396c49fe1f777\",\"name\":\"Marisha Fonseca\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.editage.com\/insights\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/f20e869af960f8daf3a3b638794b78e3f2e363b4604e2b916f9349e07bb3c01d?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/f20e869af960f8daf3a3b638794b78e3f2e363b4604e2b916f9349e07bb3c01d?s=96&d=mm&r=g\",\"caption\":\"Marisha Fonseca\"},\"url\":\"https:\/\/www.editage.com\/insights\/marisha-fonseca\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"All you need to know about repeated measures analysis in 5 minutes | Editage Insights","description":"Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results?\u00a0Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time while taking into account the correlated nature of the measurements. Read this article to find out the details.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes","og_locale":"en_US","og_type":"article","og_title":"All you need to know about repeated measures analysis in 5 minutes | Editage Insights","og_description":"Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results?\u00a0Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time while taking into account the correlated nature of the measurements. Read this article to find out the details.","og_url":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes","og_site_name":"Editage Insights","article_publisher":"https:\/\/www.facebook.com\/Editage","article_published_time":"2023-07-05T04:57:42+00:00","article_modified_time":"2025-01-15T06:21:05+00:00","og_image":[{"width":656,"height":336,"url":"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2023\/07\/pexels-fauxels-3183131-1.jpg","type":"image\/jpeg"}],"author":"Marisha Fonseca","twitter_card":"summary_large_image","twitter_creator":"@Editage","twitter_site":"@Editage","twitter_misc":{"Written by":"Marisha Fonseca","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#article","isPartOf":{"@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes"},"author":{"name":"Marisha Fonseca","@id":"https:\/\/www.editage.com\/insights\/#\/schema\/person\/d7c4142919456ea4250396c49fe1f777"},"headline":"All you need to know about repeated measures analysis in 5 minutes","datePublished":"2023-07-05T04:57:42+00:00","dateModified":"2025-01-15T06:21:05+00:00","mainEntityOfPage":{"@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes"},"wordCount":917,"commentCount":0,"publisher":{"@id":"https:\/\/www.editage.com\/insights\/#organization"},"image":{"@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage"},"thumbnailUrl":"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp","keywords":["Analysis of Data","statistical analysis","statistical reporting"],"articleSection":["Data Analysis"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes","url":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes","name":"All you need to know about repeated measures analysis in 5 minutes | Editage Insights","isPartOf":{"@id":"https:\/\/www.editage.com\/insights\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage"},"image":{"@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage"},"thumbnailUrl":"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp","datePublished":"2023-07-05T04:57:42+00:00","dateModified":"2025-01-15T06:21:05+00:00","description":"Have you ever wondered whether collecting data at multiple time points from the same set of subjects could introduce some bias into your results?\u00a0Well, repeated measures analysis is a statistical technique that allows us to examine changes in a variable over time while taking into account the correlated nature of the measurements. Read this article to find out the details.","breadcrumb":{"@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#primaryimage","url":"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp","contentUrl":"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2025\/02\/editage-insights-generic-banner_298.webp","width":656,"height":336},{"@type":"BreadcrumbList","@id":"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.editage.com\/insights\/"},{"@type":"ListItem","position":2,"name":"All you need to know about repeated measures analysis in 5 minutes"}]},{"@type":"WebSite","@id":"https:\/\/www.editage.com\/insights\/#website","url":"https:\/\/www.editage.com\/insights\/","name":"Editage Insights","description":"","publisher":{"@id":"https:\/\/www.editage.com\/insights\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.editage.com\/insights\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.editage.com\/insights\/#organization","name":"Editage Insights","url":"https:\/\/www.editage.com\/insights\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.editage.com\/insights\/#\/schema\/logo\/image\/","url":"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2024\/09\/editage-insights-logo-1-scaled.webp","contentUrl":"https:\/\/www.editage.com\/insights\/wp-content\/uploads\/2024\/09\/editage-insights-logo-1-scaled.webp","width":2560,"height":324,"caption":"Editage Insights"},"image":{"@id":"https:\/\/www.editage.com\/insights\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/Editage","https:\/\/x.com\/Editage"]},{"@type":"Person","@id":"https:\/\/www.editage.com\/insights\/#\/schema\/person\/d7c4142919456ea4250396c49fe1f777","name":"Marisha Fonseca","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.editage.com\/insights\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/f20e869af960f8daf3a3b638794b78e3f2e363b4604e2b916f9349e07bb3c01d?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/f20e869af960f8daf3a3b638794b78e3f2e363b4604e2b916f9349e07bb3c01d?s=96&d=mm&r=g","caption":"Marisha Fonseca"},"url":"https:\/\/www.editage.com\/insights\/marisha-fonseca"}]}},"_links":{"self":[{"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/posts\/4230","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/comments?post=4230"}],"version-history":[{"count":0,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/posts\/4230\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/media\/33313"}],"wp:attachment":[{"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/media?parent=4230"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/categories?post=4230"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/tags?post=4230"},{"taxonomy":"new_categories","embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/new_categories?post=4230"},{"taxonomy":"new_tags","embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/new_tags?post=4230"},{"taxonomy":"series","embeddable":true,"href":"https:\/\/www.editage.com\/insights\/wp-json\/wp\/v2\/series?post=4230"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}