Analysis Plans for Doubly Repeated Measures Designs
Robbie A. Beyl, PhD
Pennington Biomedical Research Center
Jeff Burton
Pennington Biomedical Research Center
William D. Johnson, PhD
Pennington Biomedical Research Center
Doubly repeated measures designs involve v visits, with each visit consisting of t time points. An example of this setting is the oral glucose tolerance test (OGTT), in which glucose is measured at several time points following ingestion of a glucose solution and is carried out before and after administration of a treatment. Comparing the change in the shape of the glucose curve from baseline to follow-up between two or more treatment groups is primarily the goal. A common approach used by non-statistical researchers is to ignore the baseline visit and use area under the curve (AUC) analysis to compare group curves at the follow-up visit only. Alternatively, one may analyze this type of data using a linear mixed model for repeated measures. We go over assumptions and advantages/disadvantages of AUC and mixed model analyses when using complete data versus follow-up data only.