An accessible introduction to performing meta-analysis across
various areas of research
The practice of meta-analysis allows researchers to obtain
findings from various studies and compile them to verify and form
one overall conclusion. Statistical Meta-Analysis with Applications
presents the necessary statistical methodologies that allow readers
to tackle the four main stages of meta-analysis: problem
formulation, data collection, data evaluation, and data analysis
and interpretation. Combining the authors' expertise on the topic
with a wealth of up-to-date information, this book successfully
introduces the essential statistical practices for making thorough
and accurate discoveries across a wide array of diverse fields,
such as business, public health, biostatistics, and environmental
studies.
Two main types of statistical analysis serve as the foundation
of the methods and techniques: combining tests of effect size and
combining estimates of effect size. Additional topics covered
include:
* Meta-analysis regression procedures
* Multiple-endpoint and multiple-treatment studies
* The Bayesian approach to meta-analysis
* Publication bias
* Vote counting procedures
* Methods for combining individual tests and combining individual
estimates
* Using meta-analysis to analyze binary and ordinal categorical
data
Numerous worked-out examples in each chapter provide the reader
with a step-by-step understanding of the presented methods. All
exercises can be computed using the R and SAS software packages,
which are both available via the book's related Web site. Extensive
references are also included, outlining additional sources for
further study.
Requiring only a working knowledge of statistics, Statistical
Meta-Analysis with Applications is a valuable supplement for
courses in biostatistics, business, public health, and social
research at the upper-undergraduate and graduate levels. It is also
an excellent reference for applied statisticians working in
industry, academia, and government.
