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Using This Book | |

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Introduction | |

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Narrative (Qualitative) and Meta-Analytic (Quantitative) Literature Reviews | |

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Increasing Use of Meta-Analysis | |

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Two Approaches to Conducting a Meta-Analysis | |

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Operationally Defining Abstract Concepts in Research | |

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Categorical (Qualitative) and Continuous (Quantitative) Variables | |

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Types of Variables in Research | |

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Effect-Size Measures for Categorical Variables | |

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Effect-Size Measures for Continuous Variables | |

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Some Issues to Consider When Conducting a Meta-Analysis | |

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Publication Bias and Study Quality | |

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Missing Effect-Size Estimates | |

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Fixed- and Random-Effects Models | |

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Correlated Effect-Size Estimates | |

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Using the SAS System to Conduct a Meta-Analysis | |

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References | |

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Using the SAS System to Conduct a Meta-Analysis | |

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Introduction | |

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Help for New Users of SAS Software | |

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SAS/ASSIST Software | |

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Creating a Meta-Analytic Data Set Using SAS Software | |

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Creating a Meta-Analytic Data Set from the SAS DATA Step | |

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Creating a Meta-Analytic Data Set from an OBDC Data | |

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Manipulating a SAS Data Set Using the SAS DATA Step | |

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Renaming Variables | |

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Keeping and Dropping Variables in Output SAS Data Sets | |

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Creating a Permanent SAS Data Library | |

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Using a SAS Macro | |

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Creating and Manipulating a SAS Graph | |

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SAS/GRAPH Displays on the Computer Monitor | |

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Creating a SAS/GRAPH CGM File | |

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SAS Procedures Used in This Book | |

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PROC SORT | |

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PROC PRINT | |

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PROC MEANS | |

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PROC UNIVARIATE | |

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PROC GLM | |

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PROC FORMAT | |

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PROC TIMEPLOT | |

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PROC SHEWHART | |

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Conclusions | |

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References | |

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Graphical Presentation of Meta-Analytic Results | |

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Introduction | |

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Dot Plots | |

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Funnel Plots | |

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Using a Funnel Plot to Investigate Whether All Studies Come from a Single Population | |

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Using a Funnel Plot to Search for Publication Bias | |

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Problems with Funnel Plots | |

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Normal Quantile Plots | |

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Using a Normal Quantile Plot to Check the Normality Assumption | |

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Using a Normal Quantile Plot to Investigate Whether All Studies Come from a Single Population | |

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Using a Normal Quantile Plot to Search for Publication Bias | |

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Problems with Normal Quantile Plots | |

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Stem-and-Leaf Plots | |

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Box Plots | |

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Conclusions | |

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References | |

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Appendices | |

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SAS Code for Output 3.1 | |

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SAS Macro for Finding the Minimum and Maximum Values of the Variables on the X and Y Axes | |

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SAS Macro for Entering Parameters for a Funnel Plot | |

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SAS Macro for Creating a Funnel Plot | |

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SAS Code for Figure 3.2 | |

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SAS Code Used to Create Normal Quantile Plots | |

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Combining Effect-Size Estimates Based on Categorical Data | |

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Introduction | |

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Two-Way Contingency Tables | |

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The Odds Ratio [omega] | |

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Combining Odds Ratios Using the Weighted Average Method | |

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Heterogeneity Test for Odds Ratios | |

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Combining Odds Ratios Using the Mantel-Haenszel Method | |

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Controlling for the Effects of Covariates | |

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Control by Logistic Regression | |

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Control by Stratification | |

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Conclusions | |

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References | |

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Appendices | |

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SAS Macro for Computing the Odds Ratio | |

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SAS Macro for Computing the Common Odds Ratio Based on the Weighted Average Method | |

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SAS Macro for Heterogeneity Test of Odds Ratios | |

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SAS Macro for Computing the Common Odds Ratio Based on the Mantel-Haenszel Method | |

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SAS Code for Example 4.5 | |

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Combining Effect-Size Estimates Based on Continuous Data | |

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Introduction | |

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Two Families of Effect Sizes | |

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The Standardized Mean Difference Family | |

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The Correlation Family | |

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Relationship between the Two Families of Effect Sizes | |

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Converting Test Statistics to Effect-Size Estimates and Converting Effect-Size Estimators from One Type to Another | |

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Combining Sample Standardized Mean Differences | |

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Combining Sample Correlation Coefficients | |

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Conclusions | |

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References | |

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Appendices | |

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Formulas for Converting Cohen's d, Hedges' g, and the Point-Biseral Correlation to Hedges' g[subscript U] | |

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Formulas for Converting Cohen's d, Hedges' g, and Hedges' g[subscript U] to Point-Biseral Correlations | |

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SAS Macro for Computing Effect-Size Estimates | |

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Formulas for Obtaining Hedges' g, Hedges' g[subscript U], and the Point-Biseral Correlation from a t Test Statistic | |

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SAS Macro for Converting Test Statistics to Effect-Size Estimates and for Converting Effect-Size Estimators from One to Another | |

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SAS Macro for Computing a Weighted Average of Effect-Size Estimates | |

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Vote-Counting Procedures in Meta-Analysis | |

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Introduction | |

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The Conventional Vote-Counting Procedure | |

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Level of Significance | |

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Vote-Counting Situations | |

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Vote-Counting Procedures for Estimating the Population Standardized Mean Difference | |

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Vote-Counting Procedures for Estimating the Population Correlation Coefficient | |

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Conclusions | |

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References | |

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Appendices | |

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SAS/IML Module for Obtaining the Probability of the Vote-Counting Estimate Using the Large Sample Approximation Method | |

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SAS/IML Module for Obtaining a Confidence Interval for the Population Standardized Mean Difference Using Vote-Counting Procedures | |

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SAS Macro for Obtaining a Confidence Interval for the Population Correlation Coefficient Using Vote-Counting Procedures | |

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SAS Macro for Estimating Population Effect Sizes Using Vote-Counting Procedures | |

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Combining Effect-Size Estimates and Vote Counts | |

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Introduction | |

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Using the Combined Procedure to Estimate the Population Standardized Mean Difference | |

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Using the Combined Procedure to Estimate the Population Correlation Coefficient | |

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Conclusions | |

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References | |

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Appendices | |

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SAS Code for Example 7.1 | |

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SAS Macro for Obtaining the Pearson Product-Moment Correlation Coefficient Based on the Method of Maximum Likelihood | |

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SAS Code for Example 7.2 | |

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Fixed-Effects Models in Meta-Analysis | |

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Introduction | |

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Fixed- and Random-Effects Models in Individual Experiments | |

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Fixed- and Random-Effects Models in Meta-Analysis | |

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Testing the Moderating Effects of Categorical Study Characteristics in ANOVA Models | |

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Fixed-Effects ANOVA Models with One Categorical Factor | |

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Fixed-Effects ANOVA Models with Two Categorical Factors | |

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Testing the Moderating Effects of Continuous Study Characteristics in Regression Models | |

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Confidence Intervals for Individual Regression Coefficients | |

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Omnibus Tests for Blocks of Regression Coefficients and Tests for Homogeneity of Effects | |

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Multicollinearity Among Study Characteristics | |

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Quantifying Variation Explained by Study Characteristics in ANOVA and Regression Models | |

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Conclusions | |

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References | |

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Appendices | |

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SAS Macro for Computing Q-Statistics in Fixed-Effects ANOVA Models | |

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SAS Macro for Computing Confidence Intervals for Group Mean Effects in Fixed-Effects ANOVA Models | |

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SAS Macro for Comparing Group Mean Effects in Fixed-Effects ANOVA Models | |

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SAS Macro for Computing Confidence Intervals for Regression Coefficients in Fixed-Effects Models | |

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Random-Effects Models in Meta-Analysis | |

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Introduction | |

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Testing the Moderating Effects of Categorical Study Characteristics in ANOVA Models | |

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Random-Effects Models with One Categorical Factor | |

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Random-Effects Models with Two Categorical Factors | |

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Testing the Moderating Effects of Continuous Study Characteristics in Regression Models | |

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Testing Whether the Random-Effects Variance is Zero | |

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Estimating the Random-Effects Variance | |

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Confidence Intervals for Individual Regression Coefficients | |

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Omnibus Tests for Blocks of Regression Coefficients | |

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Multicollinearity among Study Characteristics | |

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Conclusions | |

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References | |

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Combining Correlated Effect-Size Estimates | |

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Introduction | |

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Combining the Results from Multiple-Treatment Studies | |

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Combining the Results from Multiple-Endpoint Studies | |

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Conclusions | |

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References | |

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Appendices | |

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SAS Macro for Computing F[subscript MAX] Statistics for Multiple-Treatment Studies | |

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SAS Macro for Computing Combined Effect-Size Estimates and 95% Confidence Intervals in Multiple-Treatment Studies | |

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SAS Macro for Computing Combined Effect-Size Estimates and 95% Confidence Intervals in Multiple End-Point Studies | |

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Conducting and Reporting the Results of a Meta-Analysis | |

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Introduction | |

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Reporting the Results of the Literature Search | |

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Reporting the Results of the Data Collection | |

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Reporting the Results of the Data Analysis | |

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Checking Statistical Assumptions | |

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Reporting the Results of Subgroup Analyses | |

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Reporting the Results of Sensitivity Analyses | |

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Example of a Meta-Analysis | |

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Reporting the Results of the Literature Search | |

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Reporting the Results of the Data Collection | |

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Reporting the Results of the Data Analysis | |

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Conclusions about Example Meta-Analysis | |

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Conclusions | |

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References | |

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Index | |