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  • Statistical Models in Epidemiology

    Statistical Models in Epidemiology by Clayton, David; Hills, Michael;

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    Product details:

    • Publisher Oxford University Press
    • Date of Publication 8 July 1993
    • Number of Volumes laminated boards

    • ISBN 9780198522218
    • Binding Hardback
    • No. of pages384 pages
    • Size 241x162x24 mm
    • Weight 714 g
    • Language English
    • Illustrations numerous line drawings, tables
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    Short description:

    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. No previous knowledge of the subject is assumed and mathematics is deliberately kept at a manageable level. The authors introduce the concept of likelihood at the outset, and develop the theory in a highly
    visual way, making use of a large number of diagrams. Based on a highly successful course, this book explains the essential statistics for all epidemiologists.

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    Long description:

    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.

    '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

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    Table of Contents:

    I. Probability Models and Likelihood
    Probability models
    Conditional probability models
    Likelihood
    Consecutive follow-up intervals
    Rates
    Time
    Competing risks and selection
    The Gaussian probability model
    Approximate likelihoods
    Likelihood, probability, and confidence
    Null hypotheses and p-values
    Small studies
    Likelihoods for the rate ratio
    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
    The size of investigations
    II. Regression Models
    Introduction to regression models
    Poission 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
    III. Appendices
    A. Exponentials
    B. Some basic calculus
    C. Approximate profile likelihoods
    D. Table of the Chi-squared distribution
    Index

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