Repeated Measures Model

Abstract

In contrast to the previous chapters, we now assume that instead of having only one observation per object/subject (e.g., patient) we now have repeated observations. These repeated measurements are collected at previously exactly defined times. The principle idea is that these observations give information about the development of a response Y. This response might for instance be the blood pressure (measured every hour) for a fixed therapy (medicament A), the blood sugar level (measured every day of the week) or the monthly training performance of sprinters for training method A etc., that is variables which change with time (or a different scale of measurement). The aim of a design like this is not so much the description of the average behaviour of a group (with a fixed treatment), rather than the comparison of two or more treatments in their effect across the scale of measurement (e.g., time), that is the treatment or therapy comparison..