9780471558026 - Statistical Models for Causal Analysis von Retherford, Robert D.; Choe, Minja Kim (11 Ergebnisse)

Zustand: Good. 1st Edition. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Very Good. 1st Edition. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. 1st Edition. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9780471558026.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. pp. 272.

Gebunden. Zustand: New. 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.

Hardcover. Zustand: Brand New. 1st edition. 272 pages. 9.75x6.75x1.00 inches. In Stock.

Zustand: New. 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. Num Pages: 272 pages, Ill. BIC Classification: JHBC; MBNS; PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 238 x 164 x 21. Weight in Grams: 550. . 1993. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - 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 forunderstanding 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.