Drawing statistical conclusions from experiments with multiple quantitative measurements per subject

Abstract

In experiments with multiple quantitative measurements per subject, for example measurements on multiple lesions per patient, the additional measurements on the same patient provide limited additional information. Treating these measurements as independent observations will produce biased estimators for standard deviations and confidence intervals, and increases the risk of false positives in statistical tests. The problem can be remedied in a simple way by first taking the average of all observations of each specific patient, and then doing all further calculations only on the list of these patient means. A more sophisticated statistical modeling of the experiment, for example in a linear mixed model, is only required if (i) there is a large imbalance in the number of observations per patient or (ii) there is a specific interest in actually identifying the various sources of variation in the experiment.