Statistical models for causal analysis
Robert D. Retherford
Reading Time
at 250 WPM4h 34m
The average reader, reading at a speed of 250 WPM, would take 4h 34m to read Statistical models for causal analysis.
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10
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274
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Statistical models for causal analysis
Published
2011
Publisher
Wiley & Sons Canada, Limited, John
Pages
274
ISBN-13
9781282251663
Description
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.
Subjects
Multivariate data analysis
Statistical analysis for decision making
Multivariate statistical methods
Theory and application of the linear model
Using multivariate statistics
Applied regression analysis and other multivariable methods
Frequently Asked Questions
How many pages are in Statistical models for causal analysis?
This edition of Statistical models for causal analysis has approximately 274 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Statistical models for causal analysis?
For most readers, Statistical models for causal analysis typically takes between 5h 43m and 3h 48m to complete. This is based on the book's length of approximately 68,500 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 4h 34m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 10 days • Estimated word count: 68,500 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Statistical models for causal analysis?
The estimated word count for Statistical models for causal analysis is approximately 68,500 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Statistical models for causal analysis?
Statistical models for causal analysis was written by Robert D. Retherford.
When was Statistical models for causal analysis published?
The publication date for this specific edition is 2011. The original work may have been published on a different date.