Methods of Meta-Analysis: Correcting Error and Bias in Research Findings

Methods of Meta-Analysis: Correcting Error and Bias in Research Findings

by John E. Hunter, Frank L. Schmidt
     
 

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ISBN-10: 0803932227

ISBN-13: 9780803932227

Pub. Date: 12/01/1989

Publisher: SAGE Publications

Most methods of meta-analysis focus on describing and summarizing the results of studies in a research literature, but for Hunter (retired, psychology, Michigan State U.) and Schmidt (management and organization, U. of Iowa), the purpose of meta-analysis is to estimate what the results would have been had all the studies been conducted without methodological

Overview

Most methods of meta-analysis focus on describing and summarizing the results of studies in a research literature, but for Hunter (retired, psychology, Michigan State U.) and Schmidt (management and organization, U. of Iowa), the purpose of meta-analysis is to estimate what the results would have been had all the studies been conducted without methodological limitations or flaws. Since the 1990 edition, meta-analysis has become widely accepted and practiced, and their revision incorporates the new breadth. Annotation ©2004 Book News, Inc., Portland, OR

Product Details

ISBN-13:
9780803932227
Publisher:
SAGE Publications
Publication date:
12/01/1989
Pages:
592
Product dimensions:
5.51(w) x 8.66(h) x (d)

Table of Contents

Preface to 2nd Edition
Preface to 1st Edition
Acknowledgements
Introduction to Meta-Analysis
Integration Research Findings Across Studies
General problem and an example
Problems with statistical significance tests
Is statistical power the solution?
Confidence intervals
Meta-analysis
Role of meta-analysis in the behavioral and social sciences
Role of meta-analysis in theory development
Increasing use of meta-analysis
Meta-analysis in industrial-organizational psychology
Wider impact of meta-analysis on psychology
Impact of meta-analysis outside psychology
Meta-analysis and social policy
Meta-analysis and theories of data
Conclusions
Study Artifacts and Their Impact on Study Outcomes
Study Artifacts
Sampling error, statistical power, and the interpretation of research literatures
When and how to cumulate
Undercorrection for artifacts in the corrected standard deviation
Coding study characteristics and capitalization on sampling error in moderator analysis
A look ahead in the book
Meta-Analysis of Correlations
Meta-Analysis of Correlations Corrected Individually for Artifacts
Introduction and Overview
Bare bones meta-analysis: Correcting for sampling error only
Artifacts other than sampling error
Multiple simultaneous artifacts
Meta-analysis of individually corrected correlations
A worked example: Indirect range restriction
Summary of meta-analysis correcting each correlation individually
Exercise 1: Bare bones meta-analysis
Exercise 2: Meta-analysis correcting each correlation individually
Meta-Analysis of Correlations Using Artifact Distributions
Full artifact distribution meta-analysis
Accuracy of corrections for artifacts
Mixed meta-analysis: Partial artifact information in individual studies
Summary of artifact distribution of meta-analysis of correlations
Exercise: Artifact distribution meta-analysis
Technical Questions in Meta-Analysis of Correlations r versus : Which should be used?
r vs. regression slopes and intercepts in meta-analysis
Technical factors that cause overestimation of
Fixed and random models in meta-analysis
Credibility vs. confidence intervals in meta-analysis
Computing confidence intervals in meta-analysis
Range Restriction in meta-analysis: New technical analysis
Criticisms of meta-analysis procedures for correlations
Meta-Analysis of Experimental Effects and Other Dichotomous Comparisons
Treatment Effects: Experimental Artifacts and Their Impact
Quantification of the treatment effect: The d statistic and the point-biserial correlation
Sampling error in d values: Illustrations
Error of measurement in the dependent variable
Error of measurement in the treatment variable
Variation across studies in treatment strength
Range variation on the dependent variable
Dichotomization of the dependent variable
Imperfect construct validity in the dependent variable
Imperfect construct validity in the treatment variable
Bias in the effect size (d statistic)
Recording, computational, and transcriptional errors
Multiple artifacts and corrections
Meta-Analysis Methods for d Values
Effect size indices: d and r
An Alternative to d: Glass' d
Sampling error in the d statistic
Cumulation and correction of the variance for sampling error
Analysis of moderator variables
Correcting d values for measurement error in the dependent variable
Measurement error in the independent variable in experiments
Other artifacts and their effects
Correcting for multiple artifacts
Summary of meta-analysis of d values
Exercise: Meta-Analysis of d-Values
Technical Questions in Meta-Analysis of d Values
Alternative experimental designs
Within-subjects experimental designs
Meta-analysis and the within-subjects design
Statistical power in the two designs
Threats to internal and external validity
Bias in observed d values
Use of multiple regression in moderation analysis of d values
General Issues in Meta-Analysis
General Technical Issues in Meta-analysis
Fixed effects versus random effects models in meta-analysis
Second order sampling error: General principles
Detecting moderators not hypothesized a priori
Second order meta-analysis
Large N studies and meta-analysis
Second order sampling error: Technical treatment
The detection of moderator variables: Summary
Hierarchical analysis of moderator variables
Exercise: Second order meta-analysis
Cumulation of Findings Within Studies
Fully replicated designs
Conceptual replications
Conceptual replications and confirmatory factor analysis
Conceptual replications: A alternative approach
Analysis of subgroups
Summary
Methods of Integrating Findings Across Studies and Related Software
The traditional narrative procedure
The traditional voting method
Cumulation of p-values across studies
Statistically correct vote counting procedures
Meta-analysis of research studies
Unresolved problems in meta-analysis
Summary of methods of integrating studies
Computer programs for meta-analysis
Locating, Evaluating, and Coding Studies
Conducting a thorough literature search
What to do about studies with "methodological weaknesses "
Coding studies in meta-analysis
What to include in the meta-analysis report
Information needed in reports of primary studies
Appendix: Coding sheet for validity studies
Availability and Source Bias in Meta-Analysis
Some evidence on bias
Effects of methodological quality on mean effect sizes from different sources
Multiple hypotheses and other considerations in availability bias
Methods for detecting availability bias
Methods for correcting for availability bias
Summary of Psychometric Meta-Analysis
Meta-analysis methods and theories of data
What is the ultimate purpose of meta-analysis?
Appendix: Windows Based Meta-Analysis Software Package
References
Author Index
Subject Index
About the Authors

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