Journal article
Modeling Heterogeneity in Pooled Event History Analysis
State Politics & Policy Quarterly, Vol.16(1), pp.121-141
03/2016
DOI: 10.1177/1532440015592798
Abstract
Pooled event history analysis (PEHA) allows researchers to study the effects of variables across multiple policies by stacking the data and estimating the parameters in a single model. Yet this approach to modeling policy diffusion implies assumptions about homogeneity that are often violated in reality, such that the effect of a given variable is constant across policies. We relax this assumption and use Monte Carlo simulations to compare common strategies for modeling heterogeneity, testing these strategies with increasing levels of variance. We find that multilevel models with random coefficients produce the best estimates and are a significant improvement over other models. In addition, we show how modeling similar policies as multilevel structures allows researchers to more precisely explore the theoretical implications of heterogeneity across policies. We provide an empirical example of these modeling approaches with a unique data set of 29 antiabortion policies.
Details
- Title: Subtitle
- Modeling Heterogeneity in Pooled Event History Analysis
- Creators
- Rebecca J KreitzerFrederick J Boehmke
- Resource Type
- Journal article
- Publication Details
- State Politics & Policy Quarterly, Vol.16(1), pp.121-141
- Publisher
- SAGE Publications; Los Angeles, CA
- DOI
- 10.1177/1532440015592798
- ISSN
- 1532-4400
- eISSN
- 1946-1607
- Language
- English
- Date published
- 03/2016
- Academic Unit
- Political Science; Public Policy Center (Archive)
- Record Identifier
- 9983920523202771
Metrics
19 Record Views