Hardcover. Simplifies the treatment of statistical inference focusing on how to specify and interpret models in the context of testing causal theories. Simple bivariate regression, multiple regression, multiple classification analysis, path analysis, logit regression, multinomial logit regression and survival models are among the subjects covered. Features an appendix of computer programs (for major statistical packages) that are used to generate illustrative examples contained in the chapters. This volume provides an overview of statistical models commonly used in the causal analyses of non-experimental data in the social and biomedical sciences. The general principles and procedures of statistical inference and model testing are covered. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Bibliographic Details

Title: Statistical Models for Causal Analysis (Hardcover)
Publisher: John Wiley & Sons Inc, New York
Publication Date: 1994
Language: English
ISBN 10: 0471558028
ISBN 13: 9780471558026
Binding: Hardcover
Edition: 1st Edition
Condition: new

About this title

Synopsis

Simplifies the treatment of statistical inference focusing on how to specify and interpret models in the context of testing causal theories. Simple bivariate regression, multiple regression, multiple classification analysis, path analysis, logit regression, multinomial logit regression and survival models are among the subjects covered. Features an appendix of computer programs (for major statistical packages) that are used to generate illustrative examples contained in the chapters.

About the Author

Robert D. Retherford and Minja Kim Choe are the authors of Statistical Models for Causal Analysis, published by Wiley.

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