Misspecification of multimodal random‐effect distributions in logistic mixed models for panel survey data
Misspecification of multimodal random‐effect distributions in logistic mixed models for panel survey data
复制标题
面板调查数据逻辑混合模型中多模态随机效应分布的错误指定
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Haynes
中科院分区：
文献类型：
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作者：
L. Marquart;M. Haynes
纵向二元数据的逻辑混合模型通常假设正态分布的随机效应，如果存在底层子总体结构，则这可能过于严格。本文阐述了实施诊断测试和将随机效应拟合为正态分布的混合物的简便性，以检测和解决潜在的移动者-停留者场景中随机效应的分布错误指定。使用澳大利亚家庭、收入和劳动力动态小组调查的数据来说明方法。通过模拟研究评估了正态假设对以正态分布的三分量混合为特征的违规的稳健性。对于与随机效应直接相关的参数，错误地假设正态性会产生不利的推论影响，从而导致估计有偏差和置信区间的覆盖率较差。结果支持固定效应参数对随机效应的非极端分布违规的总体鲁棒性。
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.
影响因子：
1.8
作者：
Huang, Xianzheng
通讯作者：
Huang, Xianzheng