Conducting Meta-Analysis Using Sas

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Edition: 1st
Format: Nonspecific Binding
Pub. Date: 2001-06-01
Publisher(s): Psychology Pres
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Summary

Conducting Meta-Analysis Using SASreviews the meta-analysis statistical procedure and shows the reader how to conduct one using SAS. It presents and illustrates the use of the PROC MEANS procedure in SAS to perform the data computations called for by the two most commonly used meta-analytic procedures, the Hunter & Schmidt and Glassian approaches. This book serves as both an operational guide and user's manual by describing and explaining the meta-analysis procedures and then presenting the appropriate SAS program code for computing the pertinent statistics. The practical, step-by-step instructions quickly prepare the reader to conduct a meta-analysis. Sample programs available on the Web further aid the reader in understanding the material. Intended for researchers, students, instructors, and practitioners interested in conducting a meta-analysis, the presentation of both formulas and their associated SAS program code keeps the reader and user in touch with technical aspects of the meta-analysis process. The book is also appropriate for advanced courses in meta-analysis psychology, education, management, and other applied social and health sciences departments.

Author Biography

Allen I. Huffcutt is an Associate Professor of Psychology at Bradley University in Peoria, IL.

Table of Contents

List of Tables
ix
List of Figures
xiii
Preface Focus and Coverage 1(4)
The Theory of Meta-Analysis---Sampling Error and the Law of Small Numbers
5(144)
General Overview of Meta-Analysis
8(10)
Topic Selection---Defining the Research Domain
11(1)
Specifying the Inclusion Criteria
11(1)
Searching for and Locating Relevant Studies
12(1)
Selecting the Final Set of Studies
12(2)
Extracting Data and Coding Study Characteristics
14(2)
Deciding to Keep Separate or to Aggregate Multiple Data Points (Effect Sizes or Correlations) From the Same Sample---Independence and Nonindependence of Data Points
16(1)
Testing for and Detecting Outliers
17(1)
Data Analysis---Calculating Mean Effect Sizes or Correlations, Variability, and Correcting for Artifacts; Deciding to Search for Moderators; and Selecting and Testing for Potential Moderators
17(1)
Interpreting Results and Making Conclusions
17(1)
Analyzing Meta-Analytic Data and the Advantages of the SAS PROC MEANS Approach
18(2)
Summary
20(1)
Meta-Analysis of Effect Sizes
Introduction and Overview
21(1)
Calculation of Summary Statistics
22(4)
Estimation of Sampling Error Variance
26(6)
Confidence Intervals
32(2)
Correcting Summary Statistics for Artifacts---Criterion Reliability
34(2)
Chi-Square Test for Homogeneity
36(1)
SAS Printout for Training Effectiveness Example
37(2)
Meta-Analysis Results Summary Table and Interpretation of Results for Training Effectiveness Example Used in Tables 2.1, 2.2, 2.4, and 2.6
39(1)
Interpretation of Results Presented in Table 2.7
39(1)
Conducting Moderator Analysis in the Meta-Analysis of Effect Sizes
40(14)
Analysis of Moderator Variables
42(4)
Fully Hierarchical Moderator Analysis
46(7)
Interpretation of Results Presented in Table 2.13
53(1)
Summary
54(3)
Meta-Analysis of Correlations
Introduction and Overview
57(1)
Statistical Artifacts
58(4)
Sampling Error
59(1)
Error of Measurement---Independent (Predictor) and Dependent Variable (Criterion) Unreliability
59(1)
Range Variation and Restriction in the Independent and Dependent Variable
60(1)
Dichotomization of Variables
60(1)
Imperfect Construct Validity in the Independent Variable
60(1)
Imperfect Construct Validity in the Dependent Variable
61(1)
Errors in Data---Computational and Typographical Errors in Data
61(1)
Individually Corrected Versus Artifact Distribution-Based Corrections
62(1)
Interactive Versus Noninteractive Artifacts Distribution-Based Corrections
63(1)
Calculation of Summary Statistics
63(2)
Estimation of Sampling Error Variance
65(5)
Chi-Square Test for Variation Across Studies (Data Points)
70(1)
Confidence Intervals
71(4)
Correcting Summary Statistics for Multiple Attenuating Artifacts
75(10)
Artifact Distributions
78(1)
Compound Attenuation Factor
79(1)
ρ (rho)---Estimate of Fully Corrected Population Correlation
80(1)
Compound Variance Factor
81(1)
Variance due to Attenuating Artifacts
81(1)
True (Residual) Variance in rs
82(1)
Total Variance Accounted for by Sampling Error and Attenuating Artifact Factors
82(1)
Variance of ρ (rho)
83(2)
Conducting Moderator Analysis in the Meta-Analysis of Correlations
85(11)
Credibility Intervals
87(2)
Confidence Intervals
89(2)
Chi-Square Test for Homogeneity of Corrected Correlations
91(2)
Analysis of Moderator Variables
93(3)
SAS Printouts for Mental Rotation Test Validity Example
96(3)
Meta-Analysis Results Summary Table and Interpretation of Results for Mental Rotation Test Validity Example in Table 3.1 Through 3.6
99(14)
Interpretation of Results Presented in Table 3.7
103(1)
Fully Hierarchical Moderator Analysis
104(6)
Interpretation of Results Presented in Table 3.12
110(3)
Summary
113(4)
Outliers in Meta-Analytic Data
Introduction and Overview
117(1)
Outliers in Meta-Analytic Data
117(2)
The Sample-Adjusted Meta-Analytic Deviancy (SAMD) Statistic
119(4)
SAS Printouts for SAMD Examples and SAMD Scree Plots
123(1)
Summary
123(20)
Computing SAMD Values with Individually Corrected Correlations
141(1)
Computing SAMD Values with Individually Corrected Effect Sizes
141(2)
Summary and Guidelines for Implementing a Meta-Analysis
Overview
143(1)
Summary of SAS PROC MEANS Procedure
143(1)
Guidelines and Pointers
144(5)
Guideline 1
144(1)
Guideline 2
145(1)
Guideline 3
145(1)
Guideline 4
146(1)
Guideline 5
146(1)
Guideline 6
146(1)
Guideline 7
146(1)
Guideline 8
146(1)
Guideline 9
147(2)
Appendix A Reference and Information Sources for the Behavioral and Social Sciences 149(10)
Appendix B Equation for Computing the Pooled Within-Group Standard Deviation 159(2)
Appendix C Conversion and Transformation Equations 161(4)
Appendix D Upper Percentage Points for the Chi-Square Distribution 165(2)
References 167(8)
Author Index 175(4)
Subject Index 179

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