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Australian & New Zealand journal of statistics, v.61 no.2, 2019년, pp.213 - 233
Beesley, Lauren J. (Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA) , Taylor, Jeremy M. G. (Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA) , Little, Roderick J. A. (Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA)
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SummaryModels that involve an outcome variable, covariates, and latent variables are frequently the target for estimation and inference. The presence of missing covariate or outcome data presents a challenge, particularly when missingness depends on the latent variables. This missingness mechanism i...
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