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A Bayesian Multilevel Modeling Approach to Time-Series Cross-Sectional Data

A Bayesian Multilevel Modeling Approach to Time-Series Cross-Sectional Data The analysis of time-series cross-sectional (TSCS) data has become increasingly popular in political science. Meanwhile, political scientists are also becoming more interested in the use of multilevel models (MLM). However, little work exists to understand the benefits of multilevel modeling when applied to TSCS data. We employ Monte Carlo simulations to benchmark the performance of a Bayesian multilevel model for TSCS data. We find that the MLM performs as well or better than other common estimators for such data. Most importantly, the MLM is more general and offers researchers additional advantages. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Political Analysis Oxford University Press

A Bayesian Multilevel Modeling Approach to Time-Series Cross-Sectional Data

Political Analysis , Volume 15 (2) – Mar 7, 2007

A Bayesian Multilevel Modeling Approach to Time-Series Cross-Sectional Data

Political Analysis , Volume 15 (2) – Mar 7, 2007

Abstract

The analysis of time-series cross-sectional (TSCS) data has become increasingly popular in political science. Meanwhile, political scientists are also becoming more interested in the use of multilevel models (MLM). However, little work exists to understand the benefits of multilevel modeling when applied to TSCS data. We employ Monte Carlo simulations to benchmark the performance of a Bayesian multilevel model for TSCS data. We find that the MLM performs as well or better than other common estimators for such data. Most importantly, the MLM is more general and offers researchers additional advantages.

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References (32)

Publisher
Oxford University Press
Copyright
© The Author 2007. Published by Oxford University Press on behalf of the Society for Political Methodology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
ISSN
1047-1987
eISSN
1476-4989
DOI
10.1093/pan/mpm006
Publisher site
See Article on Publisher Site

Abstract

The analysis of time-series cross-sectional (TSCS) data has become increasingly popular in political science. Meanwhile, political scientists are also becoming more interested in the use of multilevel models (MLM). However, little work exists to understand the benefits of multilevel modeling when applied to TSCS data. We employ Monte Carlo simulations to benchmark the performance of a Bayesian multilevel model for TSCS data. We find that the MLM performs as well or better than other common estimators for such data. Most importantly, the MLM is more general and offers researchers additional advantages.

Journal

Political AnalysisOxford University Press

Published: Mar 7, 2007

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