A comparison of GEE and random effects models for distinguishing heterogeneity, nonstationarity and state dependence in a collection of short binary event series
Author:
Affiliation:
1. Centre for Applied Statistics, Lancaster University, Lancaster, UK,
2. Centre for Applied Statistics, Lancaster University, Lancaster, UK
Abstract
Publisher
SAGE Publications
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
http://journals.sagepub.com/doi/pdf/10.1177/1471082X0100100403
Reference28 articles.
1. Logistic regression for autocorrelated data with application to repeated measures
2. Estimation of Dynamic Models with Error Components
3. Estimating Dynamic Random Effects Models from Panel Data Covering Short Time Periods
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