Practical Epidemiology with Generalized Linear Models

This book was developed with the goal to help health researchers and biostatisticians on the use of generalized linear models applied to epidemiology. It's focused on the common epidemiological measures such as risk, incidence rate, relative risk, risk difference, incidence rate ratio and odds ratio. The book will cover person-time analysis and the use of the Binomial, Poisson, and Negative Binomial distributions. Implications of the use of the Poisson distribution to epidemiological data will be discussed, as well as the Poisson robust estimation. Generalized Estimating Equations will be shown for longitudinal clinical studies with time correlated data. It’s focused on the practical thought, although the fundamental theoretical principles have been covered.

16,98 €
15,28 € Poupe 10%

TÍTULO Practical Epidemiology with Generalized Linear Models

AUTOR Pedro Aguiar, Vera Vicente

ISBN 978-989-53988-5-0

DIMENSÃO 16cm x 23cm


ENCADERNAÇÃO Capa mole com badanas


Referências específicas


Pedro Aguiar

Statistician MSc, International Health PhD, is a professor of Epidemiology and Statistics with more than 30 years of experience as advisor in public health research and clinical epidemiology including clinical trials. His field of work and research has been mostly developed in Universities and Contract Research Organizations.  

His focus is developing the link between statistics and epidemiology. During his professional career his goal has been making the statistical language practical, accessible, and useful to health researchers, including medical doctors, nurses, and other researchers.      

Vera Vicente

Has a degree in Probabilities and Statistics from Science School of University of Lisbon and a Postgraduation in Data Analysis in the Social Sciences from ISCTE – Higher Institute of Business and Labour Sciences, Lisbon University Institute. With 15 years of experience as biostatistician, her tasks include the development of statistical methodology in clinical studies, statistical analysis plans, statistical programming (namely with SAS), and reporting of results. Vera is also involved in the preparation/review of scientific manuscripts and provides training in statistics and statistical software.


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