A simple approach to analyzing clustered longitudinal data

作者：Stephenson Matthew^*; Ali R Ayesha; Darlington Gerarda A

来源：Communications in Statistics - Simulation and Computation, 2017, 46(5): 3553-3562.

DOI：10.1080/03610918.2015.1096380

• Clustered binary data
• Cluster weighting
• Generalized estimating equations (GEE)
• Informative cluster size
• Primary 62J02 General nonlinear regression
• Secondary 62J12 Generalized linear models

When modeling correlated binary data in the presence of informative cluster sizes, generalized estimating equations with either resampling or inverse-weighting, are often used to correct for estimation bias. However, existing methods for the clustered longitudinal setting assume constant cluster sizes over time. We present a subject-weighted generalized estimating equations scheme that provides valid parameter estimation for the clustered longitudinal setting while allowing cluster sizes to change over time. We compare, via simulation, the performance of existing methods to our subject-weighted approach. The subject-weighted approach was the only method that showed negligible bias, with excellent coverage, for all model parameters.

• 出版日期2017