Advances and Applications in Statistics
Volume 16, Issue 1, Pages 1 - 15
(May 2010)
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UNDERREPORTING IN GENERALIZED POISSON REGRESSION MODEL WITH AN APPLICATION TO DEMAND FOR MEDICAL CARE DATA
Mavis Pararai
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Abstract: The assumption that is usually made when modeling count data is that the response variable is correctly reported. Some counts might be under-reported due to people not remembering when the event took place or purposefully giving a count that is less than the actual one. Underreporting of events might also be due to the sensitive nature of the question being asked. The generalized Poisson regression model for underreported counts (GPRU) will be developed. The parameters in the model will be estimated via the maximum likelihood method. The GPRU model is applied to a real-life data set. The results are compared to those of the Poisson and negative binomial regression models for underreported counts. |
Keywords and phrases: generalized Poisson regression, regression, underreporting. |
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