Linear Mixed Models for Longitudinal Data

Abstract

In medical science, studies are often designed to investigate changes in a specific parameter which is measured repeatedly over time in the participating subjects. This allows one to model the process of change within individuals. Although this process occurs in every individual, the inter subject variability can be high. For example, using data of 955 men, Brant et al showed that the average rates of increase of systolic blood pressure (SBP) are smallest in the younger age groups, and greatest in the older age groups, that obese individuals tend to have a higher SBP than non-obese individuals, and that individuals in more recent birth cohorts have lower SBP’s than those born before 1910. However, these factors are not sufficient to explain all the heterogeneity between individuals since, after correction for age, obesity and birth cohort, individuals with SBP’s above (below) average at initial examination, still have slower (faster) rates of longitudinal change in SBP.