Published February 1995
by European Communities / Union (EUR-OP/OOPEC/OPOCE) .
Written in English
|The Physical Object|
|Number of Pages||419|
This book is a guide to the practical application of statistics to data analysis in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental by: Purchase Statistical Methods for Meta-Analysis - 1st Edition. Print Book & E-Book. ISBN , Statistical met adata documents existing surveys, production systems, and production tools in such a way that these resources and experie nces can be used by designers of new surveys a nd produc Author: Bo Sundgren. The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis, and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical.
This book is dynamite: George E. P. Box, Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building It starts from zero knowledge of Statistics but it doesn't insult the reader's intelligence. It's incredibly practical but with no loss of rigour; in fact, it underscores the danger. Introduction to meta-analysis 1 (a); andPalmer and Sterne(). A book dedicated to addressing publication bias was written byRothstein, Sutton, and Borenstein(). This entry presents a general introduction to meta-analysis and describes relevant statistical Meta-analysis is the statistical-analysis step of a systematic review. General purpose statistical software varies in its ease of use and exibility for meta- analysis. These packages cannot be used “as is” because their base algorithms are designed primar-. ily for the statistical analysis of primary studies, and thus produce erroneous results applied. directly to meta- analysis. A Handbook of Statistics. Introduction to Vectors. Decision-Making using Financial Ratios. Statistics for Business and Economics. Understanding Statistics. An Introduction to Matlab. A Refresher Course in Mathematics. Introduction to statistical data analysis with R. Elementary Linear Algebra: Part I. Introduction to Probability. Matrix Algebra.
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