We present an implementation of split-population duration regression in the spduration (Beger et al., 2017) package for R that allows for time-varying covariates. The statistical model accounts for units that are immune to a certain outcome and are not part of the duration process the researcher is primarily interested in. We provide insights for when immune units exist, that can significantly increase the predictive performance compared to standard duration models. The package includes estimation and several post-estimation methods for split-population Weibull and log-logistic models. We provide an empirical application to data on military coups.
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For attribution, please cite this work as
Beger, et al., "Splitting It Up: The spduration Split-Population Duration Regression Package for Time-Varying Covariates", The R Journal, 2017
BibTeX citation
@article{RJ-2017-056,
author = {Beger, Andreas and Hill, Daniel W. and Jr., and Metternich, Nils. W. and Minhas, Shahryar and Ward, Michael D.},
title = {Splitting It Up: The spduration Split-Population Duration Regression Package for Time-Varying Covariates},
journal = {The R Journal},
year = {2017},
note = {https://doi.org/10.32614/RJ-2017-056},
doi = {10.32614/RJ-2017-056},
volume = {9},
issue = {2},
issn = {2073-4859},
pages = {474-486}
}