ANALYSING LONGITUDINAL CLAIMS COST DATA: A ZERO-AUGMENTED GAMMA MIXED REGRESSION APPROACH

• LEE Andy H.

  Department of Epidemiology and Biostatistics, School of Public Health, Curtin University of Technology

• YAU Kelvin K.W.

  Department of Management Sciences, City University of Hong Kong

Abstract

This paper presents a zero-augmented gamma mixed regression model to analyse longitudinal data with many zeros. The objective of occupational health is to reduce the injury incidence and the mean claims cost once injured. However, the population-based claims cost data often contain many zero observations (no claim). The empirical distribution thus comprises a point mass at zero mixed with a non-degenerate parametric component. The likelihood function can be factorised into two orthogonal components, corresponding to the effects of covariates on the claim incidence and the magnitude of claims, conditional on claims being made. Random effects are incorporated into the respective linear predictor to account for correlation between observations from the same individual. The mixed regression model is applied to evaluate the effectiveness of an occupational intervention program.

Journal

• Journal of the Japanese Society of Computational Statistics

  Journal of the Japanese Society of Computational Statistics 15 (2), 73-79, 2003-06-01

  Japanese Society of Computational Statistics

Keywords

• Excess zeros
• Gamma distribution
• Generalised linear mixed models
• Random effects

Details

• CRID: 1570572701954493312
• NII Article ID: 110001235164
• NII Book ID: AA10823693
• ISSN: 09152350
• Text Lang: en
• Data Source:
  • CiNii Articles