Modeling Individual Differences in Autobiographical Memory Distributions Using Mixed Logitnormal Regression. Issue 3 (2nd February 2016) - Zimprich, Daniel; Wolf, Tabea
Summary: We introduce a model for examining individual differences in the lifespan distribution of autobiographical memories (after the exclusion of recent memories). The model is based on the logitnormal distribution, contains two submodels, one for location (average age at which autobiographical memories were encoded) and one for scale (range of ages at which autobiographical memories were encoded), allows for the inclusion of predictor variables, and includes random effects. The model was used to analyze autobiographical memories reported by 90 older participants. Results show that there were reliable individual differences in location and scale. Moreover, age, proportion of positive memories, proportion of first‐time experiences, comprehensibility, and meaningfulness accounted for 26% of individual differences in location and 23% of individual differences in scale of autobiographical memory distributions. These findings indicate that individual differences are present in autobiographical memory distributions and can, in part, be accounted for by characteristics of the memories and of the person who generated them.Copyright © 2016 John Wiley & Sons, Ltd.