International Journal of Academic Medicine

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

Analysis of repeated measures data: A quick primer


Jill C Stoltzfus 
 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
USA

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.


How to cite this article:
Stoltzfus JC. Analysis of repeated measures data: A quick primer.Int J Acad Med 2016;2:95-97


How to cite this URL:
Stoltzfus JC. Analysis of repeated measures data: A quick primer. Int J Acad Med [serial online] 2016 [cited 2020 Apr 6 ];2:95-97
Available from: http://www.ijam-web.org/article.asp?issn=2455-5568;year=2016;volume=2;issue=1;spage=95;epage=97;aulast=Stoltzfus;type=0