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Statistical Models for Causal Analysis (Hardcover)
Loot Price: R5,365
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Statistical Models for Causal Analysis (Hardcover)
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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 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.
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