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• catalog abstract ""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."--Pub. desc.".
• catalog contributor b6538238.
• catalog created "c1994.".
• catalog date "1994".
• catalog date "c1994.".
• catalog dateCopyrighted "c1994.".
• catalog description ""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."--Pub. desc.".
• catalog description "1. Introduction -- Why probability models? -- Why interpretation? -- 2. Generalized linear models and the interpretation of parameters -- Generalized linear models -- Interpretation of parameter estimates -- 3. Binary logit and probit models -- Logit models -- Interpretation of logit models -- Probit models -- Interpretation of probit models -- Logit or probit models? -- 4. Sequential logit and probit models -- The model -- Interpretation of sequential logit and probit models -- 5. Ordinal logit and probit models -- The model -- Interpretation of ordinal logit and probit models -- 6. Multinomial logit models -- The model -- Interpretation of multinomial logit models -- 7. Conditional logit models -- The model -- Interpretation of conditional logit models -- 8. Poisson regression models -- The model -- Interpretation of poisson regression models -- 9. Conclusion.".
• catalog description "Includes bibliographical references.".
• catalog extent "vii, 87 p. :".
• catalog hasFormat "Interpreting probability models.".
• catalog identifier "0803949995 (pbk.)".
• catalog isFormatOf "Interpreting probability models.".
• catalog isPartOf "A Sage university papers series. Quantitative applications in the social sciences ; no. 07-101".
• catalog isPartOf "Quantitative applications in the social sciences ; no. 07-101.".
• catalog issued "1994".
• catalog issued "c1994.".
• catalog language "eng".
• catalog publisher "Thousand Oaks, Calif. : Sage,".
• catalog relation "Interpreting probability models.".
• catalog subject "519.5/38 20".
• catalog subject "Linear models (Statistics)".
• catalog subject "Logits.".
• catalog subject "Probits.".
• catalog subject "QA279 .L52 1994".
• catalog tableOfContents "1. Introduction -- Why probability models? -- Why interpretation? -- 2. Generalized linear models and the interpretation of parameters -- Generalized linear models -- Interpretation of parameter estimates -- 3. Binary logit and probit models -- Logit models -- Interpretation of logit models -- Probit models -- Interpretation of probit models -- Logit or probit models? -- 4. Sequential logit and probit models -- The model -- Interpretation of sequential logit and probit models -- 5. Ordinal logit and probit models -- The model -- Interpretation of ordinal logit and probit models -- 6. Multinomial logit models -- The model -- Interpretation of multinomial logit models -- 7. Conditional logit models -- The model -- Interpretation of conditional logit models -- 8. Poisson regression models -- The model -- Interpretation of poisson regression models -- 9. Conclusion.".
• catalog title "Interpreting probability models : logit, probit, and other generalized models / Tim Futing Liao.".
• catalog type "text".