531 to 540 of 586 Results
Kevin A. Clarke, 2010, "Replication data for: A Simple Distribution-Free Test for Nonnested Model Selection", https://doi.org/10.7910/DVN/KVMF0H, Harvard Dataverse, V1
This paper considers a simple distribution-free test for nonnested model selection. The new test is shown to be asymptotically more efficient than the well-known Vuong test when the distribution of individual log-likelihood ratios is highly peaked. Monte Carlo results demonstrate that for many applied research situations, this distribution is indee... |
Fang-Yi Chiou; Lawrence S. Rothenberg, 2010, "Replication data for: The Search for Comparability: Response to Binder", https://doi.org/10.7910/DVN/1DLOE6, Harvard Dataverse, V1
Binder (n.d., Taking the measure of Congress: Reply to Chiou and Rothenberg. Political Analysis. Forthcoming) highlights areas of agreement and disagreement with our discussion of preference measurement and legislative gridlock. We now both agree that W-NOMINATE scores—employed in Binder (1999, The dynamics of legislative gridlock. American Politic... |
Feb 22, 2010
John E. Transue; Daniel J. Lee; John H. Aldrich, 2010, "Replication data for: Treatment Spillover Effects across Survey Experiments.", https://doi.org/10.7910/DVN/YDYAZG, Harvard Dataverse, V1, UNF:5:GBGZiGBMql9AxqX0XPRdzg== [fileUNF]
Embedding experiments within surveys has reinvigorated survey research. Several survey experiments are generally embedded within a survey, and analysts treat each of these experiments as self-contained. We investigate whether experiments are self-contained or if earlier treatments affect later experiments, which we call "experimental spillover." We... |
Feb 21, 2010
Adam N. Glynn; Kevin M Quinn, 2010, "Replication data for: An Introduction to the Augmented Inverse Propensity Weighted Estimator", https://doi.org/10.7910/DVN/BIW6K5, Harvard Dataverse, V1
In this paper, we discuss an estimator for average treatment effects (ATEs) known as the augmented inverse propensity weighted (AIPW) estimator. This estimator has attractive theoretical properties and only requires practitioners to do two things they are already comfortable with: (1) specify a binary regression model for the propensity score, and... |
Donald P. Green; David H. Yoon, 2010, "Replication data for: Reconciling Individual & Aggregate Evidence Concerning Partisan Stability: Applying Time-Series Models to Panel Survey Data", https://doi.org/10.7910/DVN/NSWMR6, Harvard Dataverse, V1
Party identification has been studied extensively using both individual- and aggregate-level data. This paper attempts to formulate a statistical model that can account for the range of empirical generalizations that have emerged from aggregate time series and panel surveys. Using Monte Carlo simulation, we show that only certain types of data gene... |
Feb 17, 2010
James Honaker; Jonathan N. Katz; Gary King, 2010, "Replication data for: A Fast, Easy, & Efficient Estimator for Multiparty Electoral Data", https://doi.org/10.7910/DVN/F06OSQ, Harvard Dataverse, V1
Katz and King have previously developed a model for predicting or explaining aggregate electoral results in multiparty democracies. Their model is, in principle, analogous to what least-squares regression provides American political researchers in that two-party system. Katz and King applied their model to three-party elections in England and revea... |
Feb 17, 2010
Ben Pelzer; Rob Eisinga; Philip Hans Franses, 2010, "Replication data for: Inferring Transition Probabilities from Repeated Cross Sections", https://doi.org/10.7910/DVN/MKJ5EN, Harvard Dataverse, V1
This paper discusses a nonstationary, heterogeneous Markov model designed to estimate entry and exit transition probabilities at the micro level from a time series of independent cross-sectional samples with a binary outcome variable. The model has its origins in the work of Moffitt and shares features with standard statistical methods for ecologic... |
Feb 17, 2010
John O'Loughlin, 2010, "Replication data for: The Electoral Geography of Weimar Germany: Exploratory Spatial Data Analyses (ESDA) of Protestant Support for the Nazi Party", https://doi.org/10.7910/DVN/2JHJFF, Harvard Dataverse, V1
For more than half a century, social scientists have probed the aggregate correlates of the vote for the Nazi party (NSDAP) in Weimar Germany. Since individual-level data are not available for this time period, aggregate census data for small geographic units have been heavily used to infer the support of the Nazi party by various compositional gro... |
Bruce Western; Meredith Kleykamp, 2010, "Replication data for: A Bayesian Change Point Model for Historical Time Series Analysis", https://doi.org/10.7910/DVN/KGAYVB, Harvard Dataverse, V1
Political relationships often vary over time, but standard models ignore temporal variation in regression relationships. We describe a Bayesian model that treats the change point in a time series as a parameter to be estimated. In this model, inference for the regression coefficients reflects prior uncertainty about the location of the change point... |
Michael C. Herron, 2010, "Replication data for: Post-Estimation Uncertainty in Limited Dependent Variable Models", https://doi.org/10.7910/DVN/DRTT1H, Harvard Dataverse, V1, UNF:3:8yagqQgJhSqOCpU1rUnYYA== [fileUNF]
Many political science research articles that use limited dependent variable models report estimated quantities, in particular, fitted probabilities, predicted probabilities, and functions of such probabilities, without indicating that such estimates are subject to uncertainty. This practice, along with the reporting of "percentage correctly predic... |
