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Statistical models in epidemiology

Author: David Clayton; Michael Hills
Publisher: Oxford ; New York : Oxford University Press, 1993.
Series: Oxford science publications.
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
Summary:
This self-contained account of the statistical basis of epidemiology has been written for those with a basic training in biology. It is specifically intended for students enrolled for a masters degree in epidemiology, clinical epidemiology, or biostatistics.
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: David Clayton; Michael Hills
ISBN: 0198522215 9780198522218
OCLC Number: 27975013
Description: viii, 367 pages : illustrations ; 24 cm.
Contents: Probability models --
Conditional probability models --
Likelihood --
Consecutive follow-up intervals --
Rates --
Time --
Competing risks and selection --
Gaussian probability model --
Approximate likelihoods --
Likelihood, probability, and confidence --
Null hypotheses and p-values --
Small studies --
Likelihoods for the rate ration --
Confounding and standardization --
Comparison of rates within strata --
Case-control studies --
Likelihoods for the odds ratio --
Comparison of odds within strata --
Individually matched case-control studies --
Tests for trend --
Size of investigations --
Introduction to regression models --
Poisson and logistic regression --
Testing hypotheses --
Models for dose-response --
More about interaction --
Choice and interpretation of models --
Additivity and synergism --
Conditional logistic regression --
Cox's regression analysis --
Time-varying explanatory variables --
Three examples --
Nested case-control studies --
Gaussian regression models --
Postscript --
Exponentials and logarithms --
Some basic calculus --
Approximate profile likelihoods. (cont) Table of the chi-squared distribution.
Series Title: Oxford science publications.
Responsibility: David Clayton and Michael Hills.
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Abstract:

Suitable for those with a basic training in biology, this book shows how all statistical analysis of data is based on probability models, and once one understands the model, analysis follows easily.  Read more...

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'Unlike many textbooks in epidemiology, there is no long wordy preamble. The characteristic style is set straight away. The book is also highly successful in presenting a unified approach. What is Read more...

 
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