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

About the Author

David Clayton, Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research Michael Hills, London School of Hygiene and Tropical Medicine

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