Interpreting Probability Models | Logit, Probit, and Other Generalized Linear Models

Tim Futing Liao

ISBN 10: 0803949995 / ISBN 13: 9780803949997

Published by Sage Publications, Inc, 1994

About this Item

Interpreting Probability Models | Logit, Probit, and Other Generalized Linear Models | Tim Futing Liao | Taschenbuch | Kartoniert / Broschiert | Englisch | 1994 | Sage Publications, Inc | EAN 9780803949997 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 102381480

Bibliographic Details

• Title: Interpreting Probability Models | Logit, Probit, and Other Generalized Linear Models
• Publisher: Sage Publications, Inc
• Publication Date: 1994
• Language: English
• ISBN 10: 0803949995
• ISBN 13: 9780803949997
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 216W x 140H x 6D millimeters 216 millimeters width by 140 millimeters height by 6 millimeters depth
• Weight: 135 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

"The author provides a stepwise approach for evaluating the results of fitting probability models to data as the focus for the book . . . . All this is packaged very systematically . . . . the booklet is highly successful in showing how probability models can be interpreted."

--Technometrics

"Tim Futing Liao′s Interpreting Probability Models. . . is an advanced text . . . . Liao′s text is more theoretical, but is well exemplified using case studies . . . . this is a text for the more advanced statistician or the political scientist with strong leanings in this direction!"

--John G. Taylor in Technology and Political Science

What is the probability that something will occur, and how is that probability altered by a change in some independent variable? Aimed at answering these questions, Liao introduces a systematic way for interpreting a variety of probability models commonly used by social scientists. Since much of what social scientists study are measured in noncontinuous ways and thus cannot be analyzed using a classical regression model, it is necessary for scientists to model the likelihood (or probability) that an event will occur. This book explores these models by reviewing each probability model and by presenting a systematic way for interpreting results. Beginning with a review of the generalized linear model, the book covers binary logit and probit models, sequential logit and probit models, ordinal logit and probit models, multinomial logit models, conditional logit models, and Poisson regression models.

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.