Applied Meta-Analysis With R And Stata Av Ding-Geng (Din) (University Of North Carolina Usa) Chen, Karl E. (Georgia Southern University Usa) Peace

<P><STRONG>Review of the First Edition:</STRONG></P><I><P>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.</P></I><P>¿<STRONG><EM>Journal of Applied Statistics</EM></STRONG></P><I><P>Statistical Meta-Analysis with R and Stata, Second Edition</I> 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