Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Introduction to Meta-Analysis
This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Introduction to Meta-Analysis: Outlines the role of meta-analysis in the research process Shows how to compute effects sizes and treatment effects Explains the fixed-effect and random-effects models for synthesizing data Demonstrates how to assess and interpret variation in effect size across studies Clarifies concepts using text and figures, followed by formulas and examples Explains how to avoid...
Doing Meta-Analysis with R
Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the ...
The Future of Meta-Analysis
Scientific progress often begins with the difficult task of preparing informed, conclusive reviews of existing research. Since the 1970s, the traditional "subjective" approach to research reviewing in the social sciences has been challenged by a statistical alternative known as meta-analysis. Meta-analysis provides a principled method of distilling reliable generalizations from previous studies on a single topic, thereby providing a quantitative and objective background for future research. The Future of Meta-Analysis brings together expert researchers for an in-depth examination of this new methodology—not to promote a consensus view but rather to explore from several perspectives the the...
Meta-Analysis
Author Fredric M. Wolf explains how to use combined statistical tests and measures of effect size to synthesize the results of independent studies of a common research question.
Meta-Analysis with R
This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.
Individual Participant Data Meta-Analysis
Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points. Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appra...
Statistical Methods for Meta-Analysis
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. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.
Meta-Study of Qualitative Health Research
This title provides step-by-step directions for how to conduct a meta-study, as well as recommendations for tools and standards for the application of this approach.
Advanced Basic Meta-analysis
In response to the growing emphasis on precision in the summarization and integration of research literature, Advanced BASIC Meta-Analysis presents an overview of strategies, techniques, and procedures used in meta-analysis. The book and software provide an integrated and comprehensive combination of meta-analytic tools for the statistical integration of independent study results. Advanced BASIC Meta-Analysis has three distinct goals: * to provide a clear and user-friendly introduction to the procedures and rules of effective meta-analytic integration; * to present the implicit assumptions and strategies that guide successful meta-analytic integrations; and * to develop a meta-analytic datab...
Network Meta-Analysis for Decision-Making
A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question "for this pre-identified population of patients, which treatment is 'best'?" A co...
