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Updated: Aug 20, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Modeling road accident fatalities with underdispersion and zero-inflated counts.
Teerawat Simmachan1,2, Noppachai Wongsai2, Sangdao Wongsai1,2
1Faculty of Science and Technology, Department of Mathematics and Statistics, Thammasat University, Pathum Thani, Thailand.
Thailand experiences high road accident fatalities (RAFs), particularly during festivals. This study reveals that focusing on festival safety is less effective than promoting nationwide awareness of everyday road risks.
Area of Science:
- Epidemiology
- Statistics
- Public Health
Background:
- Thailand faces a critical road safety challenge, ranking second globally in road accident fatalities (RAFs) in 2013.
- Road traffic accidents (RTAs) and RAFs significantly increase during the Songkran festival, yet festivity-specific factors remain understudied.
Purpose of the Study:
- To investigate the contributing factors to road accident fatalities (RAFs) in Thailand.
- To apply and compare various count regression models for analyzing RAF data.
- To evaluate the effectiveness of current road safety strategies during festival periods.
Main Methods:
- Utilized a dataset of 20,229 accidents in Thailand from 2015.
- Applied Poisson, Conway-Maxwell-Poisson (CMP), and their zero-inflated (ZI) versions to model RAF data.
- Analyzed the influence of road, weather, environmental, and temporal factors on accident outcomes.
Main Results:
- RAFs in Thailand exhibited a rare count distribution with underdispersion and excessive zeros.
- The Zero-Inflated Conway-Maxwell-Poisson (ZICMP) model showed a marginal improvement over the CMP model.
- Road, weather, and environmental factors influenced RAFs across all accidents, while the month differentiated non-fatal accidents from fatal ones.
Conclusions:
- The choice of statistical model is crucial and depends on the specific research question.
- Festival-specific road safety interventions may be less effective than broad, nationwide awareness campaigns.
- Public perception of road safety risks may be inaccurate, necessitating a shift towards promoting everyday personal safety and awareness.
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