501 to 510 of 586 Results
Mar 7, 2010
Robert Berrens; Alok Bohara; Hank Jenkins-Smith; Carol Silva; David Weimer, 2010, "Replication data for: The Advent of Internet Surveys for Political Research: A Comparison of Telephone and Internet Samples", https://doi.org/10.7910/DVN/SVYYAP, Harvard Dataverse, V1
The Internet offers a number of advantages as a survey mode: low marginal cost per completed response, capabilities for providing respondents with large quantities of information, speed, and elimination of interviewer bias. Those seeking these advantages confront the problem of representativeness both in terms of coverage of the population and capa... |
Mar 7, 2010
Frederick J. Boehmke, 2010, "Replication data for: Using Auxiliary Data to Estimate Selection Bias Models, with an Application to Interest Group Use of the Direct Initiative Process", https://doi.org/10.7910/DVN/RMSOVN, Harvard Dataverse, V1
Recent work in survey research has made progress in estimating models involving selection bias in a particularly difficult circumstance—all nonrespondents are unit nonresponders, meaning that no data are available for them. These models are reasonably successful in circumstances where the dependent variable of interest is continuous, but they are l... |
Mar 7, 2010
Simon Hug, 2010, "Replication data for: Selection Bias in Comparative Research: The Case of Incomplete Data Sets", https://doi.org/10.7910/DVN/QO28VG, Harvard Dataverse, V1
Selection bias is an important but often neglected problem in comparative research. While comparative case studies pay some attention to this problem, this is less the case in broader cross-national studies, where this problem may appear through the way the data used are generated. The article discusses three examples: studies of the success of new... |
Mar 7, 2010
Micah Altman; Michael McDonald, 2010, "Replication data for: Replication with Attention to Numerical Accuracy", https://doi.org/10.7910/DVN/J2PCGQ, Harvard Dataverse, V1
Numerical issues matter in statistical analysis. Small errors occur when numbers are translated from paper and pencil into the binary world of computers. Surprisingly, these errors may be propagated and magnified through binary calculations, eventually producing statistical estimates far from the truth. In this replication and extension article, we... |
Mar 7, 2010
Michael C. Herron; Kenneth W. Shotts, 2010, "Replication data for: Using Ecological Inference Point Estimates as Dependent Variables in Second-Stage Linear Regressions", https://doi.org/10.7910/DVN/CEXDMV, Harvard Dataverse, V1
The practice of using point estimates produced by the King ecological inference technique as dependent variables in second-stage linear regressions leads to second-stage results that, in general, are inconsistent. This conclusion holds even when all assumptions behind King's ecological technique are satisfied. Second-stage inconsistency is a conseq... |
Janet Box-Steffensmeier; Suzanna De Boef; Kyle Joyce, 2010, "Replication data for: Event Dependence and Heterogeneity in Duration Models: The Conditional Frailty Model", https://doi.org/10.7910/DVN/S38FOU, Harvard Dataverse, V1, UNF:5:zNr/tRPkrgnvnXAb2cy3XA== [fileUNF]
We introduce the conditional frailty model, an event history model that separates and accounts for both event dependence and heterogeneity in repeated events processes. Event dependence and heterogeneity create within-subject correlation in event times thereby violating the assumptions of standard event history models. Simulations show the advantag... |
Garrett Glasgow, 2010, "Replication data for: Mixed Logit Models for Multiparty Elections", https://doi.org/10.7910/DVN/PCPVWB, Harvard Dataverse, V1
Mixed logit (MXL) is a general discrete choice model thus far unexamined in the study of multicandidate andmultiparty elections. Mixed logit assumes that the unobserved portions of utility are a mixture of an IID extreme value term and another multivariate distribution selected by the researcher. This general specification allows MXL to avoid impos... |
Ethan Katz, 2010, "Replication data for: Bias in Conditional and Unconditional Fixed Effects Logit Estimation", https://doi.org/10.7910/DVN/QFNUJO, Harvard Dataverse, V1
Fixed-effects logit models can be useful in panel data analysis, when N units have been observed for T time periods. There are two main estimators for such models: unconditional maximum likelihood and conditional maximum likelihood. Judged on asymptotic properties, the conditional estimator is superior. However, the unconditional estimator holds se... |
Lee Sigelman; Langche Zeng, 2010, "Replication data for: Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models", https://doi.org/10.7910/DVN/JDZ3P5, Harvard Dataverse, V1
Political scientists are making increasing use of the Tobit and Heckit models. This paper addresses some common problems in the application and interpretation of these models. Through numerical experiments and reanalysis of data from a study by Romer and Snyder (1994), we illustrate the consequences of using the standard Tobit model, which assumes... |
R. Michael Alvarez; Garrett Glasgow, 2010, "Replication data for: Two-Stage Estimation of Nonrecursive Choice Models", https://doi.org/10.7910/DVN/AXTRI7, Harvard Dataverse, V1
Questions of causation are important issues in empirical research on political behavior. Most of the discussion of the econometric problems associated with multiequation models with reciprocal causation has focused on models with continuous dependent variables (e.g., Markus and Converse 1979; Page and Jones 1979). Yet, many models of political beha... |
