Journal of Biometrics & Biostatistics

Stef van Buuren

Publications

• Commentary
  Doubly Robust Imputation of Incomplete Binary Longitudinal Data
  Author(s): Shahab Jolani and Stef van BuurenShahab Jolani and Stef van Buuren
  
  Estimation in binary longitudinal data by using generalized estimating equation (GEE) becomes complicated in the presence of missing data because standard GEEs are only valid under the restrictive missing completely at random assumption. Weighted GEE has therefore been proposed to allow the validity of GEE's under the weaker missing at random assumption. Multiple imputation offers an attractive alternative, by which the incomplete data are pre-processed, and afterwards the standard GEE can be applied to the imputed data. Nevertheless, the imputation methodology requires correct specification of the imputation model. Dual imputation method provides a new way to increase the robustness of imputations with respect to model misspecification. The method involves integrating the so-called doubly robust ideas into the imputation model. Focusing on incomplete binary longitudinal data, we comb.. Read More»
  DOI: 10.4172/2155-6180.1000194

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