Frequency of Indian Health Insurance Claims Data using Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) Regression Models

Authors

  • Srimannarayana Gajula
  • Lalitha P S
  • Kiran Kumar Paidipati

Keywords:

Indian Health Insurance, Gender Priority, Poisson, frequency Claims, Zero- Inflated Poisson Regression, Zero-Inflated Negative Binomial Regression,

Abstract

The study focused on Indian health insurance claims using the ZIP model (Zero-Inflated Poisson) ZINB model (Zero-Inflated Negative Binomial) and Poisson regression analysis used for measuring the zero-Inflated count data. Frequency of claiming insurance modelled the regression analysis with gender priorities and the situations. The analysis consists of two basic situations based on frequency of claims and priorities of gender. To check the models whether fitted or valid using AIC and -2 Log – likelihood measures and Vuong test statistics to compare the fitted models. The ZIP and ZINB regression models suit for above mentioned situations, to compare the (females and males), secondly (females and males with others, transgenders)

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References

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Published

2023-09-30

How to Cite

Gajula, S. ., P S, L., & Paidipati, K. K. . (2023). Frequency of Indian Health Insurance Claims Data using Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) Regression Models. The Journal of Contemporary Issues in Business and Government, 29(3), 237–246. Retrieved from https://cibgp.com/au/index.php/1323-6903/article/view/2595

Issue

Vol. 29 No. 3 (2023): The journal of contemporary issues in business and government

Section

Articles

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