Modeling zero-inflated count series with application to occupational health
Related Experiment Video
Updated: Aug 26, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Kelvin K W Yau1, Andy H Lee, Philip J W Carrivick
1Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China.
Abstract:
A zero-inflated Poisson mixed autoregression model is presented for analyzing time series of count events with excess zeros. The model is motivated by the evaluation of a participatory ergonomics intervention intended to reduce manual handling workplace injuries over a specified time period. Random effects are introduced into the linear predictor of the model to account for serial correlation between successive observations. Parameter estimation is achieved by maximizing an appropriate log-likelihood function to obtain approximate residual maximum likelihood estimates. The method enables the evaluation of occupational intervention using population level aggregated count data series containing extra zeros.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Mechanistic Models: Compartment Models in Individual and Population Analysis
Assumptions of Survival Analysis
Data Collection by Observations
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Models of Health Promotion and Illness Prevention II
The agent-host-environment model states that disease results from...