# Statistical Models in Epidemiology

## Clayton, D. — Hills, M.

### ISBN-13: 9780199671182

### OXFORD

Enero / 2013

1ª Edición

Inglés

384 pags

1000 gr

16 x 23 x cm

Recíbelo en un plazo De 2 a 3 semanas

### About this book

- Essential statistics for all epidemiologists
- All mathematics is kept at a manageable level for those without specialist training in statistics
- Makes statistical analysis simple and satisfying

This self-contained account of the statistical basis of epidemiology has been written specifically for those with a basic training in biology, therefore no previous knowledge is assumed and the mathematics is deliberately kept at a manageable level. The authors show how all statistical analysis of data is based on probability models, and once one understands the model, analysis follows easily.

In showing how to use models in epidemiology the authors have chosen to emphasize the role of likelihood, an approach to statistics which is both simple and intuitively satisfying. More complex problems can then be tackled by natural extensions of the simple methods. Based on a highly successful course, this book explains the essential statistics for all epidemiologists.

Readership: Students enrolled in masters degree courses on epidemiology/clinical epidemiology, or biostatistics.

### Reviews

"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 also striking, is that the authors have managed to say something useful and clear about many of the all too numerous minor problems that are inevitably encountered in practice. In my view this is simply an excellent text. " - Andrew Pickles, Institute of Psychiatry, London, Statistical Methods in Medical Research 1994:3

"An excellent text which provides the simplest and most logical exposition that I have seen of the statistical foundations for current techniques for analysing epidemiological data, and provides an excellent preparation for more detailed treatments. " - Australasian Epidemiological Association News, 12/94

"Provides probably the most coherent and logical exposition of the use of statistical models in epidemiology that is currently available ... an excellent text which provides the simplest and most logical exposition that I have seen of the statistical foundations for current techniques for analysing epidemiological data, and provides an excellent preparation for more detailed treatments. " - AEA News 12/94

"Clayton and Hills have filled the gap with an interesting text which is based mainly on probability models and likelihood. This is an unusual approach. but is precisely what is missing in many other textbooks for epidemiologists ... this is an important text for those interested in understanding statistical reasoning in epidemiology. " - Maria Blettner, International Journal of Epidemiology

"The authors have produced a text that will be extremely valuable to those teaching epidemiologic methods... Statistical Models in Epidemiology courageously cuts new paths into the traditional epidemiologic approach to statistical training. " - Journal of the American Statistics Association

"This book gives some very clear explanations ... Each point is well illustrated with small examples and there are exercises throughout. It is pleasing to see full solution to all the exercises. " - Public Health (1994) 108

### Table of contents

**I. Probability Models and Likelihood**

1: Probability models

2: Conditional probability models

3: Likelihood

4: Consecutive follow-up intervals

5: Rates

6: Time

7: Competing risks and selection

8: The Gaussian probability model

9: Approximate likelihoods

10: Likelihood, probability, and confidence

11: Null hypotheses and p-values

12: Small studies

13: Likelihoods for the rate ratio

14: Confounding and standardization

15: Comparison of rates within strata

16: Case-control studies

17: Likelihoods for the odds ratio

18: Comparison of odds within strata

19: Individually matched case-control studies

20: Tests for trend

21: The size of investigations

**II. Regression Models**

22: Introduction to regression models

23: Poission and logistic regression

24: Testing hypotheses

25: Models for dose-response

26: More about interaction

27: Choice and interpretation of models

28: Additivity and synergism

29: Conditional logistic regression

30: Cox's regression analysis

31: Time-varying explanatory variables

32: Three examples

33: Nested case-control studies

34: Gaussian regression models

35: Postscript

**III. Appendices**

A. Exponentials

B. Some basic calculus

C. Approximate profile likelihoods

D. Table of the Chi-squared distribution

Index

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