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  3. Mathematik, Informatik und Statistik - Open Access LMU - Teil 01/03 Podcast
  4. Cross-sectional Analysis of Longitudinal Data with Missing Values in the Dependent Variables: A Comparison of Weighted Estimating Equations with the Complete Case Analysis
Inference for cross-sectional models using longitudinal data can be
drawn with independence estimating equations (Liang and Zeger,
1986). Many studies suffer from missing data. Robins and coworkers
proposed to use weighted estimating equations (WEE) in estimating
the mean structure, if missing data are present in dependent
variables. In this paper the WEE are compared with complete case
analyses for binary responses using simulated data. Our results are
in accordance with the theoretical findings of Robins and
coworkers. The WEE yield consistent estimates, even if the data are
missing at random.

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