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Some considerations for excess zeroes in substance abuse research
Dipankar Bandyopadhyay1, Stacia M DeSantis, Jeffrey E Korte
1Division of Biostatistics and Epidemiology, Department of Medicine, Medical University of South Carolina, Charleston, 29425, USA. bandyopd@gmail.com
The American Journal of Drug and Alcohol Abuse
|August 23, 2011
Summary
Hurdle models offer a better approach than zero-inflated models for analyzing substance use data with excess zeroes. Age and study participation significantly impact cocaine use behavior.
Area of Science:
- Statistical modeling in substance abuse research
- Count data analysis with excess zeroes
Background:
- Substance abuse research frequently encounters count data with numerous zeroes.
- Zero-inflated regression models are common but may overlook study design implications.
- Alternative statistical approaches are needed to address excess zeroes effectively.
Purpose of the Study:
- To demonstrate hurdle models as a viable alternative to zero-inflated models.
- To validate a two-stage decision-making process for data with excess zeroes.
- To analyze cocaine use frequency in dependent subjects.
Main Methods:
- Utilized data from 45 cocaine-dependent subjects.
- Analyzed the frequency of cocaine use days per week (bounded count data).
- Compared binomial, Poisson, negative binomial, and hurdle versions of these models.
Main Results:
- The hurdle binomial model showed the best fit for the data.
- Gender and time were not significant predictors of cocaine use.
- Age was associated with increased odds of use initially, then decreased odds with further use.
- Study participation was linked to higher odds of no cocaine use and reduced odds of further use.
Conclusions:
- Age and study participation are significant predictors of cocaine use behavior.
- Hurdle binomial models provide valuable insights into covariate effects on substance use count data, especially when subjects are at risk.
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