Statistical methods for environmental epidemiology with R :
Peng, Roger D
Statistical methods for environmental epidemiology with R : a case study in air pollution and health / Roger D. Peng and Francesca Dominici - New York : Springer, 2008 - ix, 144 p. 24 cm.
This book provides an overview of the methods used for investigating the health effects of air pollution and gives examples and case studies in R which demonstrate the application of those methods to real data. The book will be useful to statisticians, epidemiologists, and graduate students working in the area of air pollution and health and others analyzing similar data. The authors describe the different existing approaches to statistical modeling and cover basic aspects of analyzing and understanding air pollution and health data. The case studies in each chapter demonstrate how to use R to apply and interpret different statistical models and to explore the effects of potential confounding factors. A working knowledge of R and regression modeling is assumed. In-depth knowledge of R programming is not required to understand and run the examples.
9780387781662
Air--Pollution--Mathematical models.
Environmental health.
R (Computer program language)
363.7392 / PEN
Statistical methods for environmental epidemiology with R : a case study in air pollution and health / Roger D. Peng and Francesca Dominici - New York : Springer, 2008 - ix, 144 p. 24 cm.
This book provides an overview of the methods used for investigating the health effects of air pollution and gives examples and case studies in R which demonstrate the application of those methods to real data. The book will be useful to statisticians, epidemiologists, and graduate students working in the area of air pollution and health and others analyzing similar data. The authors describe the different existing approaches to statistical modeling and cover basic aspects of analyzing and understanding air pollution and health data. The case studies in each chapter demonstrate how to use R to apply and interpret different statistical models and to explore the effects of potential confounding factors. A working knowledge of R and regression modeling is assumed. In-depth knowledge of R programming is not required to understand and run the examples.
9780387781662
Air--Pollution--Mathematical models.
Environmental health.
R (Computer program language)
363.7392 / PEN