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Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models: 101 (Quantitative Applications in the Social Sciences) - Softcover
Synopsis
What is the probability that something will occur, and how is that probability altered by a change in an independent variable? To answer these questions, Tim Futing Liao introduces a systematic way of interpreting commonly used probability models. Since much of what social scientists study is measured in noncontinuous ways and, therefore, cannot be analyzed using a classical regression model, it becomes necessary to model the likelihood that an event will occur. This book explores these models first by reviewing each probability model and then by presenting a systematic way for interpreting the results from each.
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About the Author
Tim Liao is Professor of Sociology & Statistics. His research interests include historical/comparative sociology, demography, and methodology. He is a former Deputy Editor of The Sociological Quarterly, (1992-2000) and the current Editor of Sage’s Quantitative Applications in the Social Sciences series. He served on the council of the ASA Methodology Section (1998-2001) and on the council of the North America Chinese Sociological Association (2000-2002). He has been on the editorial board of Sociological Methods & Research since 1994 and on the editorial board of Sociological Methodology since 2003. He is the Chair-Elect of the Methodology Section of the American Sociology Association from August 2007 to August 2009.
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Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models (Quantitative Applications in the Social Sciences)
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