Produkt
Klappentext
Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data.
It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data.
With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software.
Features useful commands for describing a data table composed made up of quantitative and qualitative variables
Includes measures of association encountered in epidemiological studies, odds ratio, relative risk, and prevalence
Presents an analysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon), and the Cox regression model
Christophe Lalanne started working in experimental psychology and psychophysics (visual perception and motor control), and neurosciences. During his PhD, he became progressively interested in statistical methods related to behavioral measurement. After his PhD, he becam a psychometrician in educational testing and biomedical research. His main interests involve categorical data analysis, item-response theory, automatic reporting, multivariate data analysis and visualization.
Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data.
It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data.
With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software.
Features useful commands for describing a data table composed made up of quantitative and qualitative variables
Includes measures of association encountered in epidemiological studies, odds ratio, relative risk, and prevalence
Presents an analysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon), and the Cox regression model
Christophe Lalanne started working in experimental psychology and psychophysics (visual perception and motor control), and neurosciences. During his PhD, he became progressively interested in statistical methods related to behavioral measurement. After his PhD, he becam a psychometrician in educational testing and biomedical research. His main interests involve categorical data analysis, item-response theory, automatic reporting, multivariate data analysis and visualization.