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Item type | Location | Call Number | Status | Date Due |
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E-Book | AUM Main Library | 519.5 (Browse Shelf) | Not for loan |
Rationale and overview of the book -- Complexities of primary research and meta-analysis -- Fixed, random, and mixed models -- Correlations -- Effect sizes -- Proportion/odds ratio data -- Dependence in primary research and meta-analysis -- Correlations -- Effect sizes (group comparisons and change measures) -- Proportion/odds ratio data -- Bayesian approaches -- Missing data -- Combining across designs -- Qualitative studies in synthesis -- Quality assessments -- Studies on quality weighting -- Summary/Conclusions.
.Meta-analysis is used increasingly in the social sciences to synthesize research results. As both primary research and the questions addressed by meta-analysis have been grown more complex, meta-analysis techniques have evolved to address these issues. This book covers a number of advances in meta-analysis that are not covered in detail in many introductory books on research synthesis. More specifically, this book discusses the planning of a meta-analysis for complex questions, computing power for tests in meta-analysis, handling missing data in meta-analysis, integrating individual data into a traditional meta-analysis and generalizing from the results of a meta-analysis. For each topic, a fully annotated example is provided with sample computer programs for the major statistical packages. This book assumes a familiarity with basic meta-analytic techniques. The goal of the book is to provide researchers with advanced strategies for strengthening the planning, conduct and interpretations of meta-analysis with complex data.
Terri D. Pigott is a Professor of Research Methodology in Loyola University Chicago’s School of Education. Her research interests are in developing new methods for meta-analysis, and the use of meta-analysis in public policy..
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