17,391 to 17,400 of 17,402 Results
Feb 15, 2010
John D. Huber; Georgia Kernell; Eduardo L. Leoni, 2010, "Replication data for: Institutional Context, Cognitive Resources and Party Attachments Across Democracies", https://doi.org/10.7910/DVN/T6UN5A, Harvard Dataverse, V1
This paper develops and tests arguments about how national-level social and institutional factors shape the propensity of individuals to form attachments to political parties. Our tests employ a two-step estimation procedure that has attractive properties when there is a binary dependent variable in the first stage and when the number of second-lev... |
Dec 20, 2009
Gary King, 2009, "On Political Methodology", https://doi.org/10.7910/DVN/4C5GJN, Harvard Dataverse, V1
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Dec 20, 2009
Charles H. Franklin, 2009, "Estimation across Data Sets: Two-Stage Auxiliary Instrumental Variables Estimation (2SAIV)", https://doi.org/10.7910/DVN/HL5YUY, Harvard Dataverse, V1
Theories demand much of data, often more than a single data collection can provide. For example, many important research questions are set in the past and must rely on data collected at that time and for other purposes. As a result, we often find that the data lack crucial variables. Another common problem arises when we wish to estimate the relati... |
Dec 20, 2009
John E. Jackson, 2009, "An Errors-in-Variables Approach to Estimating Models with Small Area Data", https://doi.org/10.7910/DVN/5DL20N, Harvard Dataverse, V1
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Dec 20, 2009
John Zaller, 2009, "Bringing Converse Back In: Modeling Information Flow in Political Campaigns", https://doi.org/10.7910/DVN/PJ7CVB, Harvard Dataverse, V1
In his 1962 paper, "Information Flow and the Stability of Partisan Attitudes," Converse explained why moderately sophisticated voters are sometimes most susceptible to persuasion in election campaigns. Such people, Converse argued, pay enough attention to campaigns to be fairly heavily exposed to persuasive messages but lack the sophistication to b... |
Dec 20, 2009
Stanley Feldman, 2009, "Measuring Issue Preferences: The Problem of Response Instability", https://doi.org/10.7910/DVN/OMXKJQ, Harvard Dataverse, V1
The problem of response instability in survey measures of policy positions has been studied for over 20 years without any apparent resolution. Two major interpretations remain: Philip Converse's nonattitudes model and a measurement error model. One reason why neither interpretation has as yet been rejected or well supported is that previous analyse... |
Dec 20, 2009
Nathaniel Beck, 2009, "Estimating Dynamic Models Using Kalman Filtering", https://doi.org/10.7910/DVN/TRRVNY, Harvard Dataverse, V1
The Kalman filter is useful to estimate dynamic models via maximum likelihood. To do this the model must be set up in state space form. This article shows how various models of interest can be set up in that form. Models considered are Auto Regressive-Moving Average (ARMA) models with measurement error and dynamic factor models. The filter is used... |
Dec 20, 2009
Thomas Piazza; Paul M. Sniderman; Philip Tetlcok, 2009, "Analysis of the Dynamics of Political Reasoning: A General-Purpose Computer-Assisted Methodology", https://doi.org/10.7910/DVN/A2IOEH, Harvard Dataverse, V1
The purpose of this article is to present a methodology for better gauging the nature and dynamics of social and political attitudes. Starting from a particular view of attitude assessment, we show how computer-assisted interviewing can help transform the survey interview from a passive to an interactive process. Since the ultimate test of a method... |
Dec 20, 2009
Lutz Erbring, 2009, "Individuals Writ Large: An Epilogue on the "Ecological Fallacy"", https://doi.org/10.7910/DVN/CAMT5L, Harvard Dataverse, V1
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Dec 20, 2009
John R. Freeman, 2009, "Systematic Sampling, Temporal Aggregation, and the Study of Political Relationships", https://doi.org/10.7910/DVN/6JINVU, Harvard Dataverse, V1
Systematic sampling and temporal aggregation are the practices of sampling a time series at regular intervals and of summing or averaging time series observations over a time interval, respectively. Both practices are a source of statistical error and faulty inference. The problems that systematic sampling and temporal aggregation create for the co... |