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Item Details
Title: APPLIED META-ANALYSIS WITH R
By: Ding-Geng (Din) Chen, Karl E. Peace
Format: Hardback

List price: £84.99


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 1466505990
ISBN 13: 9781466505995
Publisher: TAYLOR & FRANCIS INC
Pub. date: 30 April, 2013
Series: Chapman & Hall/CRC Biostatistics Series
Pages: 342
Synopsis: In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data.Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R) in public health, medical research, governmental agencies, and the pharmaceutical industry.
Illustrations: 31 black & white illustrations, 11 black & white tables
Publication: US
Imprint: CRC Press Inc
Returns: Returnable
Some other items by this author:
APPLIED META-ANALYSIS WITH R
APPLIED META-ANALYSIS WITH R AND STATA
BIOPHARMACEUTICAL SEQUENTIAL STATISTICAL APPLICATIONS
BIOPHARMACEUTICAL SEQUENTIAL STATISTICAL APPLICATIONS (HB)
CLINICAL TRIAL BIOSTATISTICS AND BIOPHARMACEUTICAL APPLICATIONS
CLINICAL TRIAL BIOSTATISTICS AND BIOPHARMACEUTICAL APPLICATIONS (HB)
CLINICAL TRIAL DATA ANALYSIS USING R
CLINICAL TRIAL DATA ANALYSIS USING R (HB)
CLINICAL TRIAL DATA ANALYSIS USING R AND SAS
CLINICAL TRIAL DATA ANALYSIS USING R AND SAS (HB)
CLINICAL TRIAL METHODOLOGY
CLINICAL TRIAL METHODOLOGY
CLINICAL TRIAL METHODOLOGY (HB)
DATA AND SAFETY MONITORING COMMITTEES IN CLINICAL TRIALS (HB)
DESIGN AND ANALYSIS OF CLINICAL TRIALS WITH TIME-TO-EVENT ENDPOINTS
DESIGN AND ANALYSIS OF CLINICAL TRIALS WITH TIME-TO-EVENT ENDPOINTS (HB)
INNOVATIVE STATISTICAL METHODS FOR PUBLIC HEALTH DATA (HB)
INTERVAL-CENSORED TIME-TO-EVENT DATA
INTERVAL-CENSORED TIME-TO-EVENT DATA (HB)
MONTE-CARLO SIMULATION-BASED STATISTICAL MODELING (HB)
MULTIPLE TESTING ADJUSTMENT IN CLINICAL TRIALS AND GENETIC EPIDEMIOLOGY STUDIES WITH R
MULTIPLE TESTING ADJUSTMENT IN CLINICAL TRIALS AND GENETIC EPIDEMIOLOGY STUDIES WITH R (HB)
STATISTICAL ANALYSIS OF MICROBIOME DATA WITH R
STATISTICAL ANALYSIS OF MICROBIOME DATA WITH R (HB)
STATISTICAL ANALYTICS FOR HEALTH DATA SCIENCE WITH SAS AND R (HB)
STATISTICAL CAUSAL INFERENCES AND THEIR APPLICATIONS IN PUBLIC HEALTH RESEARCH (HB)
STATISTICAL ISSUES IN DRUG RESEARCH AND DEVELOPMENT (HB)
STATISTICAL META-ANALYSIS USING R AND STATA (HB)
STATISTICAL MODELING FOR DEGRADATION DATA (HB)
STATISTICAL REGRESSION MODELING WITH R
STATISTICAL REGRESSION MODELING WITH R (HB)
STRUCTURAL EQUATION MODELING USING R/SAS (HB)

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