Journal of the Royal Statistical Society: Series A (Statistics in Society)

Misspecification of multimodal random‐effect distributions in logistic mixed models for panel survey data

Journal Article

Summary 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.

Related Topics

Related Publications

Related Content

Site Footer


This website is provided by John Wiley & Sons Limited, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ (Company No: 00641132, VAT No: 376766987)

Published features on are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.