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Year : 2016  |  Volume : 2  |  Issue : 1  |  Page : 95-97

Analysis of repeated measures data: A quick primer

The Research Institute, St. Luke's University Health Network, Bethlehem; Temple University School of Medicine, Philadelphia, PA, USA

Correspondence Address:
Jill C Stoltzfus
St. Luke's University Health Network, 801 Ostrum Street, Bethlehem, PA 18015
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2455-5568.183320

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When analyzing data for dependent groups (e.g., before and after intervention), one use repeated measures statistical tests that account for the correlated observations. For normally distributed data measured on a continuous/interval scale (e.g., fasting glucose) with only two points of measurement (e.g., before and after), one would conduct a paired t-test. For more than two measurement points (e.g., baseline, 3 months, 6 months), repeated measures analysis of variance is appropriate. For skewed continuous/interval data (e.g., body mass index in the general population), or ordinal data (e.g., visual analog pain scores), one could conduct a Wilcoxon signed-rank test (for two measurement points) or a Friedman's test (for more than two measurement points). The following core competencies are addressed in this article: Medical knowledge.

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