Journal of Official Statistics, Vol.27, No.2, 2011. pp. 255277

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A Pseudo-GEE Approach to Analyzing Longitudinal Surveys under Imputation for Missing Responses

This article presents a pseudo-GEE approach to the analysis of longitudinal surveys when the response variable contains missing values. A cycle-specific marginal hot-deck imputation method is proposed to fill in the missing responses and a pseudo-GEE method is applied to the imputed data set. Consistency of the resulting pseudo-GEE estimators is established under a joint randomization framework. Linearization variance estimators are also developed for the pseudo-GEE estimators under the assumption that the finite population sampling fraction is small or negligible. Finite sample performances of the proposed estimators are investigated through an extensive simulation study using data from the National Longitudinal Survey of Children and Youth.

Complex sampling design, consistency, generalized estimating equations, joint randomization, hot-deck imputation, superpopulation model, variance estimation

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