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Pamela Paxton
Researcher at University of Texas at Austin
Publications - 91
Citations - 11024
Pamela Paxton is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Politics & Democracy. The author has an hindex of 44, co-authored 89 publications receiving 9831 citations. Previous affiliations of Pamela Paxton include Ohio State University & University of North Carolina at Chapel Hill.
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Is social capital declining in the united states? a multiple indicator assessment
TL;DR: In this paper, a model of social capital that has explicit links to theories of Social capital was proposed and analyzed over a 20-year period, showing that the results do not consistently support Putnam's claim of a decline in social capital.
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An Empirical Evaluation of the Use of Fixed Cutoff Points in RMSEA Test Statistic in Structural Equation Models
TL;DR: There is little empirical support for the use of .05 or any other value as universal cutoff values to determine adequate model fit, regardless of whether the point estimate is used alone or jointly with the confidence interval.
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Social Capital and Democracy: An Interdependent Relationship
TL;DR: In this article, the relationship between social capital and democracy is tested using data from a large, quantitative, cross-national study, and results show that social capital affects democracy and that democracy affects social capital.
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Conceptualizing and Measuring Democracy: A New Approach
Michael Coppedge,Michael Coppedge,John Gerring,David Altman,Michael Bernhard,M. Steven Fish,Allen Hicken,Matthew Kroenig,Staffan I. Lindberg,Kelly M. McMann,Pamela Paxton,Holli A. Semetko,Svend-Erik Skaaning,Jeffrey K. Staton,Jan Teorell +14 more
TL;DR: In this article, the authors argue for an approach to conceptualize and measure regimes such that meaningful comparisons can be made through time and across countries, and review some of the payoffs such an approach might bring to the study of democracy.
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Improper Solutions in Structural Equation Models Causes, Consequences, and Strategies
TL;DR: In this paper, the authors examine the most common type of improper solutions: zero or negative error variances, and address the causes of, consequences of, and strategies to handle these issues.