To test whether personality is associated with the rate of change of BMI, we used HLM (Raudenbush & Bryk, 2002; Singer & Willett, 2003) to model change in BMI across the 52 years of the longitudinal study for all participants with at least one valid personality assessment (n = 1,988). HLM is a flexible approach that can be applied to evaluate within-individual change or growth trajectories. In HLM analyses, the number and spacing of measurement observations may vary across persons, given that the time-series observations in each individual are used to estimate each individual’s trajectory (Level 1), and those individual parameters are the basis of group estimates (Level 2). Even data from individuals who were tested on only a single occasion can be used to stabilize estimates of the mean and variance. In this way, all available data can be included in the analyses. This is a major advantage of conducting analyses within the HLM framework; by contrast, missing data and varying timing pose major problems in conventional repeated measures analyses of variance (ANOVA). Furthermore, longitudinal HLM can estimate age trajectories over a broad age span with data collected in a relatively shorter time interval.
