Title | Predicting Censored Count Data with COM-Poisson Regression |
Publication Type | Working Paper |
Year of Publication | 2010 |
Authors | Sellers, K. F., and G. Shmueli |
Series Title | Working Paper RHS 06-129 |
Institution | Smith School of Business, University of Maryland |
Abstract | Censored count data are encountered in many applications, often due to a data collection mechanism that introduces censoring. A common example is questionnaires with question answers of the type 0,1,2,3+. We consider the problem of predicting a censored output variable Y , given a set of complete predictors X. The common solution would be to use adaptations for Poisson or negative binomial regression models that account for the censoring. We study two alternatives that allow for |
URL | http://ssrn.com/abstract=1702845 |
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