International Journal of

Clinical Biostatistics and BiometricsISSN: 2469-5831


 Open Access DOI:10.23937/2469-5831/1510009

Hierarchical Bayes Approach for Analysis of Item-Level Missing Data

Junshan Qiu and Ram Tiwari

Article Type: Research Article | First Published: June 30, 2016

Missing data are primarily due to dropout which can be categorized into different types based on its relation to the response process. For simplicity, it is generally assumed that the relation between a specific type of dropout and the response process can be described using a single (indicator) random variable. In case of distinct types of dropout, it is natural to use the multinomial indicator variables to model the dropout....

Volume 2
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