Unifying Political Methodology The Likelihood Theory of Statistical Inference
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Description: One of the hallmarks of the development of political science as a discipline has been the creation of new methodologies by scholars within the discipline--methodologies that are well-suited to the analysis of political data. Gary King has been a leader in the development of these new approaches to the analysis of political data. In his book, Unifying Political Methodology, King shows how the likelihood theory of inference offers a unified approach to statistical modeling for political research and thus enables us to better analyze the enormous amount of data political scientists have collected over the years. Newly reissued, this book is a landmark in the development of political methodology and continues to challenge scholars and spark controversy. "Gary King's Unifying Political Methodology is at once an introduction to the likelihood theory of statistical inference and an evangelist's call for us to change our ways of doing political methodology. One need not accept the altar call to benefit enormously from the book, but the intellectual debate over the call for reformation is likely to be the enduring contribution of the work." --Charles Franklin, American Political Science Review "King's book is one of the only existing books which deal with political methodology in a clear and consistent framework. The material in it is now and will continue to be essential reading for all serious students and researchers in political methodology." --R. Michael Alvarez, California Institute of Tech-nology Gary King is Professor of Government, Harvard University. One of the leading thinkers in political methodology, he is the author of A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data and other books and articles.
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Copyright year: 1998
Publisher: University of Michigan Press
Publication date: 6/24/1998
Size: 6.25" wide x 9.25" long x 1.00" tall
|Conceptualizing uncertainty and inference|
|The probability model of uncertainty|
|The likelihood model of inference|
|Discrete regression models|
|Models for tabular data|
|Time series models|
|Introduction to multiple equation models|
|Models with nonrandom selection|
|General classes of multiple equation models|