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Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software
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Applied Meta-Analysis with R and Stata (Hardcover, 2nd edition)
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Applied Meta-Analysis with R and Stata (Hardcover, 2nd edition)
Series: Chapman & Hall/CRC Biostatistics Series
Expected to ship within 12 - 17 working days
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Review of the First Edition: The authors strive to reduce theory to
a minimum, which makes it a self-learning text that is
comprehensible for biologists, physicians, etc. who lack an
advanced mathematics background. Unlike in many other textbooks, R
is not introduced with meaningless toy examples; instead the reader
is taken by the hand and shown around some analyses, graphics, and
simulations directly relating to meta-analysis... A useful hands-on
guide for practitioners who want to familiarize themselves with the
fundamentals of meta-analysis and get started without having to
plough through theorems and proofs. -Journal of Applied Statistics
Statistical Meta-Analysis with R and Stata, Second Edition provides
a thorough presentation of statistical meta-analyses (MA) with
step-by-step implementations using R/Stata. The authors develop
analysis step by step using appropriate R/Stata functions, which
enables readers to gain an understanding of meta-analysis methods
and R/Stata implementation so that they can use these two popular
software packages to analyze their own meta-data. 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/Stata packages and functions. What's New in the
Second Edition: Adds Stata programs along with the R programs for
meta-analysis Updates all the statistical meta-analyses with
R/Stata programs Covers fixed-effects and random-effects MA,
meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five
new chapters on multivariate MA, publication bias, missing data in
MA, MA in evaluating diagnostic accuracy, and network MA 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 or Stata) in
public health, medical research, governmental agencies, and the
pharmaceutical industry.
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