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....
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