Comparing Zero-inflated Poisson, Zero-inflated Negative Binomial and Zero-inflated Geometric in Count Data with Excess Zero
Asian Journal of Probability and Statistics,
Count data often violate the assumptions of a normal distribution due to the fact that they are bounded by their lowest value which is zero. The Poison distribution is sometimes suggested but when the assumption of equal mean and variance is violated due to over-dispersion and presence of zeros we tend to look in the direction of other models. Zero-inflated data falls in this category. The zero-inflated and hurdle models have been found to fit this scenario. The proportions of zero in the data often affect the choice of the models. Our study used the Monte Carlo design to sample 1000 cases from positively skewed distribution with 1.25 as mean vector and 0.10 as zero-inflation parameter. The data was analysed using the method of the maximum likelihood estimation. The Zero-Inflated Poisson, Zero-Inflated Negative Binomial and Zero-Inflated Geometric were fitted; the standard error and Akaike Information Criterion were obtained as measures of model validation with ZIP outperformed ZINB and ZIG.
How to Cite
Delucchi KL, Bostrom A. Methods for analysis of skewed data distributions in psychiatric clinical studies: Working with many zero values. American Journal of Psychiatry. 2004;161:1159-1168.
Famoye F, Singh K. Zero-inflated generalized Poisson regression model with an application to domestic violence data. Journal of Data Science. 2006;4:117-130.
Agresti A. An introduction to categorical data analysis. New York: John Wiley An Application to Domestic Violence Data. Journal of Data Science. 1996;4:117-130.
Zorn CJW. Evaluating zero-inflated and hurdle Poisson specifications. Midwest Political Science Association. 1996;1-16.
Bryk AS, Raudenbush SW, Congdon RT. HLM: Hierarchical linear Cambridge University Press; 1996. Cameron AC, Trivedi PK. Regression analysis of count data. New York: CB2 8RU, UK, Published in the United States of America by Cambridge; 1998.
Colin A, Trivedi. Regression of count data: Cambridge University Press 0521632013; 1998.
Colin A, Trivedi. Essentials of count regression. Online Publication; 1999.
Abstract View: 2045 times
PDF Download: 1026 times