Statistical models for causal analysis

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Last edited by MARC Bot
July 24, 2024 | History

Statistical models for causal analysis

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Free of unwieldy mathematics, Statistical Models for Causal Analysis provides a lucid introduction to statistical models used in the social and biomedical sciences, particularly those models used in the causal analysis of nonexperimental data.

Featuring an approach that focuses on model specification and interpretation, this innovative work-designed specifically for students and professionals in need of a working knowledge of the subject - is a practice-oriented guide to learning how to use these models in analytical work.

Based on a highly successful classroom course, Statistical Models for Causal Analysis includes computer programs implementable on either mainframe computers or microcomputers as well as examples taken from an actual population study. The book provides not only a clear understanding of principles of model construction but also a working knowledge of how to implement these models using real data.

Topics covered are bivariate linear regression, multiple regression, multiple classification analysis, path analysis, logit regression, multinomial logit regression, survival models (including proportional hazard models and hazard models with time dependence).

While omitting a good deal of difficult mathematics, such as derivations of sampling distributions and standard errors, the book nonetheless provides a rigorous and focused examination of model specification and interpretation, illustrating their application to the kinds of research that social and biomedical scientists undertake.

Supported by numerous tables and graphs, using real survey data, as well as an appendix of computer programs for the statistical packages SAS, BMDP, and LIMDEP, the book is an ideal primer for understanding and using statistical models in analytical work.

Eminently clear and highly practical, Statistical Models for Causal Analysis is essential for social science and biomedical professionals wishing to upgrade their methodological skills and students in need of a challenging, yet simplified treatment, of these useful, versatile models that have become essential tools for the modern researcher in these fields.

Publish Date
Publisher
Wiley
Language
English
Pages
258

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Previews available in: English

Edition Availability
Cover of: Statistical Models for Causal Analysis
Statistical Models for Causal Analysis
2011, Wiley & Sons, Incorporated, John
in English
Cover of: Statistical Models for Causal Analysis
Statistical Models for Causal Analysis
2011, Wiley & Sons, Incorporated, John
in English
Cover of: Statistical Models for Causal Analysis
Statistical Models for Causal Analysis
2011, Wiley & Sons Canada, Limited, John
in English
Cover of: Statistical models for causal analysis
Statistical models for causal analysis
1993, Wiley
in English

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Book Details


Edition Notes

Includes bibliographical references (p. 251-253) and index.
"A Wiley-Interscience publication."

Published in
New York

Classifications

Dewey Decimal Class
519.5/35
Library of Congress
QA278 .R47 1993, QA278.R47 1993

The Physical Object

Pagination
xiv, 258 p. :
Number of pages
258

ID Numbers

Open Library
OL1414072M
Internet Archive
statisticalmodel00reth_479
ISBN 10
0471558028
LCCN
93023423
OCLC/WorldCat
28722620
Library Thing
3120218
Goodreads
2907961

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History

Download catalog record: RDF / JSON
July 24, 2024 Edited by MARC Bot import existing book
May 13, 2020 Edited by ImportBot import existing book
December 4, 2010 Edited by Open Library Bot Added subjects from MARC records.
April 28, 2010 Edited by Open Library Bot Linked existing covers to the work.
December 10, 2009 Created by WorkBot add works page