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arXiv · 2105.00504

Variable selection for longitudinal survey data

Laura Dumitrescu·Wei Qian·J. N. K. Rao
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Abstract

In this article we propose a new variable selection method for analyzing data collected from longitudinal sample surveys. The procedure is based on the survey-weighted quadratic inference function, which was recently introduced as an alternative to the survey-weighted generalized estimating function. Under the joint model-design framework, we introduce the penalized survey-weighted quadratic inference estimator and obtain sufficient conditions for the existence, weak consistency, sparsity and asymptotic normality. To illustrate the finite sample performance of the model selection procedure, we include a limited simulation study.

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Laura Dumitrescu, Wei Qian, J. N. K. Rao. 2021-05-02. Variable selection for longitudinal survey data. https://arxiv.org/abs/2105.00504

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