Zero-inflated poisson quasi-Lindley regression for modeling number of doctor visit data

The Poisson regression is a popular approach in modeling count data. However, many situations often the variance of data greater than mean (over-dispersed data) and generalized or mixed models such as gamma (negative binomial), inverse Gaussian, lognormal, Lindley have been proposed alternatives to for describing over-dispersed In some situations, source over-dispersion large percentage zeros dataset. other words, dataset involves an excessive number are expected common discrete distributions which known zero-inflated events. order analyze these data, Poisson, negative binomial applied. This work proposes functional form model quasi-Lindley (ZIPQL) then, beside alternative models, it was fitted compared US National Medical Expenditure Survey