Meta-Analysis
Chapter
Abstract
The objective of scientific investigations is to gain knowledge and understanding about phenomena through careful and systematic observations and analyses. Arguably, scientific research has an inherent cumulative nature since dependable information of prior scientific inquiries guides future studies as well as facilitates knowledge building.
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References
- Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. Chichester West Sussex, U.K.: Wiley.CrossRefGoogle Scholar
- Cohn, L. D., & Becker, B. J. (2003). How meta-analysis increases statistical power. Psychological Methods, 8, 243–253.CrossRefGoogle Scholar
- Cook, T. D., Cooper, H., Cordray, D., Hartmann, H., Hedges, L., Light, R., Louis, T., Mosteller, F. (Eds.). (1992). Meta-Analysis for explanation: A casebook. New York: Russell Sage Foundation.Google Scholar
- Cooper, H. (1989). Integrating research (2nd Ed.). Newbury Park, CA: Sage Publications.Google Scholar
- Cooper, H., Hedges, L. V., & Valentine, J. C. (2009). The handbook of research synthesis and metaanalysis (2nd Ed.). New York: Russell Sage.Google Scholar
- Cooper, H., Valentine, J. C., Charlton, K., & Melson, A. (2003). The effects of modified school calendars on student achievement and on school and community attitudes: A research synthesis. Review of Educational Research, 73, 1–52.CrossRefGoogle Scholar
- DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled Clinical Trials, 7, 177–188.CrossRefGoogle Scholar
- Garvey, W., & Griffith, B. (1971). Scientific communication: Its role in the conduct of research and creation of knowledge. American Psychologist, 26, 349–361.CrossRefGoogle Scholar
- Fleiss, J. L. (1994). Measures of effect size for categorical data. Pages 245–260 in H. Cooper and L. V. Hedges, The handbook of research synthesis. New York: The Russell Sage Foundation.Google Scholar
- Glass, G. V. (1976). Primary, secondary, and meta-analysis. Educational Researcher, 5, 3–8.CrossRefGoogle Scholar
- Hedges, L. V. (1983). A random effects model for effect sizes. Psychological Bulletin, 93, 388–395.CrossRefGoogle Scholar
- Hedges, L. V. (2009). Statistical considerations. In H. Cooper, L. V. Hedges, & J. C. Valentine, The handbook of research synthesis and meta-analysis (pp. 357–376). New York: Russell Sage.Google Scholar
- Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando, FL: Academic Press.Google Scholar
- Hedges, L. V., & Vevea, J. L. (1998). Fixed and random effects models in meta analysis. Psychological Methods, 3, 486–504.CrossRefGoogle Scholar
- Konstantopoulos, S. (2011). Fixed effects and variance components estimation in three-level metaanalysis? Research Synthesis Methods, 2, 61–76.CrossRefGoogle Scholar
- Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.Google Scholar
- Littell, R. C., Milliken, G. A., Stroup, W. W., & Wolfinger, R. D. (1996). SAS system for mixed models. Cary, NC: SAS Institute INC.Google Scholar
- Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models. Newbury Park, CA: Sage.Google Scholar
- Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimentaldesigns for generalized causal inference. Boston, MA: HoughtonMifflin.Google Scholar
- Singer, J. D. (1998). Using SAS PROC MIXED to fit multilevel growth models, hierarchical models, and individual growth models. Journal of Educational and Behavioral Statistics, 24, 323–355.CrossRefGoogle Scholar
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