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Misspecification of multimodal random-effect distributions in logistic mixed models for panel survey data
Marquart, Louise Haynes, Michele
Marquart, Louise
Haynes, Michele
Author
Abstract
Logistic mixed models for longitudinal binary data typically assume normally distributed random effects, which may be too restrictive if an underlying subpopulation structure exists. The paper illustrates the ease of implementing diagnostic tests and fitting random effects as a mixture of normal distributions to detect and address distributional misspecification of the random effects in a potential mover–stayer scenario. Methods are illustrated by using data from the Household, Income and Labour Dynamics in Australia panel survey. The robustness of the normality assumption to violations characterized by a three‐component mixture of normal distributions was assessed via a simulation study. Adverse inferential impact of incorrectly assuming normality was identified for parameters directly related to the random effects, resulting in biased estimates and poor coverage rates for confidence intervals. The results support the general robustness of fixed effect parameters to non‐extreme distributional violations of the random effects.
Keywords
Household, Income and Labour Dynamics in Australia survey, Misspecified random effects, Mover–stayer scenario, Multimodal random effects, Random-intercept logistic model
Date
2019
Type
Journal article
Journal
Journal of the Royal Statistical Society Series A: Statistics in Society
Book
Volume
182
Issue
1
Page Range
305-321
Article Number
ACU Department
Institute for Learning Sciences and Teacher Education (ILSTE)
Faculty of Education and Arts
Faculty of Education and Arts
Relation URI
Source URL
Event URL
Open Access Status
License
File Access
Controlled