Meta-Analytic Structural Equation Modeling Technique
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Abstract
This article reports the study of statistical analysis using Meta-Analytic Structural Educational Model (MASEM) proposed by Cheung (2009, 2010). The case study based on component synthesis of educational leadership from 4 dissertations with 17 observed variables and 4 latent variables. Total sample size was 2,370. The process had 3 stages. Stage one was data preparation by entering correlation matrices from each research into program variables. Stage two was homogeneity test and calculating the pooled correlation matrix. And stage three was structural educational model analysis based on the pooled correlation matrix. The calculation from R program reported good-of-fitness indices in appropriate level. This case study had gone through analysis process and found that Meta-Analytic Structural Educational Model is a good meta-analysis technique for researches.
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References
Brown, S. P., & Peterson, R. A. (1993). Antecedents and consequences of salesperson job satisfaction: Meta-analysis and assessment of causal effects. Journal of Marketing Research, 30(1), 63 – 77.
Carson, P. P., Carson, K. D., & Roe, C. W. (1993). Social Power Bases: A Meta - Anaiytic Examination of Interrelationships and Outcomes1. Journal of Applied Social Psychology, 23(14), 1150 - 1169.
Cheung, M.W.L. & Chan, W. (2005). Meta-analytic structural equation modeling: a two-stage approach. Psychological Methods, 10(1), 40.
Cheung, M.W.L. (2009a). Meta – analysis: A Structural Equation Modeling Perspective. Paper presented at the Association for Psychological Science 21st Annual Convention, San Francisco, CA, USA.
Cheung, M.W.L. (2009b). Modeling multivariate effect sizes with structural equation models. Structural Equation Modeling, 17(3), 481 - 509.
Cheung, M.W.L. (2010). Fixed-effects meta-analyses as multiple-group structural equation models. Structural Equation Modeling, 17, 481 -509.
Colquitt, J. A., LePine, J. A., & Noe, R. A. (2000). Toward an integrative theory of training motivation: A meta-analytic path analysis of 20 years of research. Journal of Applied Psychology, 85, 678 –707.
Cudeck, R. (1989), "Analysis of Correlation Matrices Using Covariance Structure Models," Psychological Bulletin, 105(2), 317 - 327.
Furlow, C.F., & Beretvas, S.N. (2005). Meta-analytic methods of pooling correlation matrices for structural equation modeling under different patterns of missing data. Psychological Methods, 10, 227 - 254.
Generalized Least Square (n.d.).In Wikipedia. (Online) Retrieved from : http://en.wikipedia.org/wiki/Generalized_least_squares. [2015, March 24].
Glass, G. V., MacGaw, B., & Smith, M. L. (1984). Meta - analysis in social research. Beverly Hills, CA. : Sage.
Hafdahl, A.R. (2001). Multivariate meta-analysis for exploratory factor analytic research. Unpublished doctoral dissertation, University of North Carolina at Chapel Hill.
Hedges, L. & Olkin, I. (1985). Statistical models for meta-analysis. New York : Academic Press.
Hom, P.W., Caranikas-Walker, F., Prussia, G.E., & Griffeth, R.W. (1992). A meta-analytical structural equations analysis of a model of employee turnover. Journal of Applied Psychology, 77(6), 890.
Hunter, J. E. (1983). A causal analysis of cognitive ability, job knowledge, job performance, and supervisor ratings. In F. Landy, S. Zedeck, and J. Cleveland (Eds.), Performance measurement and theory. Hillsdale, NJ : Erlbaum. 257 – 266.
Hunter, J. E., Schmidt, F. L., & Jackson, G. B. (1982). Meta-analysis: Cumulating research findings across studies, 4.
Hunter, J.E., & Schmidt, F.L. (1990). Methods of meta–analysis: Correcting error and bias in research findings. Newbury Park, CA : Sage.
Hunter, J.E. & Schmidt, F.L. (2004). Methods of meta-analysis: Correcting error and bias in research findings. (2nded.). Thousand Oaks, CA : Sage.
Jöreskog, K.G. & Sörbom, D. (1996). LISREL 8 user's reference guide. Scientific Software International.
Mullen, B. (1989). Advance BASIC meta - analysis. Hillsdale, NJ : Erlbaum.
Premack, S. L. & Hunter, J. E. (1988). Individual unionization decisions. Psychological Bulletin, 103(2), 223.
Rosenthal, R. (1991). Essentials of behavioral research: Methods and data analysis. Mc Graw - Hill Humanities Social.
Schmidt, F. L. Hunter, J. E., & Outerbridge, A. N. (1986). Impact of job experience and ability on job knowledge, work sample performance, and supervisory ratings of job performance. Journal of applied psychology, 71(3), 432.
Silver, N.C. & Dunlap, W.P. (1987). Averaging correlation coefficients: should Fisher's z transformation be used? Journal of Applied Psychology, 72(1), 146.
Slavin, R. E. (1986). Best-evidence synthesis: An alternative to meta-analytic and traditional reviews. Educational researcher, 15(9), 5 - 11.
Tangutairuang, T. (2015). Meta-Analysis SEM in Leadership. (Online) Retrieved from : http://www.slideshare.net/twatchait/meta-analysisseminleadership. [2015, May 20].
Tett, R. P. & Meyer, J. P. (1993). Job satisfaction, organizational commitment, turnover intention, and turnover: Path analyses based on meta-analytic findings. Personnel Psychology, 46, 259 – 290.
Viswesvaran, C. & Ones, D.S. (1995). Theory testing: combining psychometric meta - analysis and structural equations modeling. Personnel Psychology, 48(4), 865 - 885.
Wilson, D.B. (2015). Meta - analysis macros for SAS, SPSS, and Stata. (Online) Retrieved from : http://mason.gmu.edu/~dwilsonb/ma.html. [2015, May 3].
Wiratchai, N. & Wongwanich, S. (1998). Educational Research Synthesis with Meta-Analysis and Content Analysis. The Office of Education Commission, Bangkok, Thailand. (in Thai)
Carson, P. P., Carson, K. D., & Roe, C. W. (1993). Social Power Bases: A Meta - Anaiytic Examination of Interrelationships and Outcomes1. Journal of Applied Social Psychology, 23(14), 1150 - 1169.
Cheung, M.W.L. & Chan, W. (2005). Meta-analytic structural equation modeling: a two-stage approach. Psychological Methods, 10(1), 40.
Cheung, M.W.L. (2009a). Meta – analysis: A Structural Equation Modeling Perspective. Paper presented at the Association for Psychological Science 21st Annual Convention, San Francisco, CA, USA.
Cheung, M.W.L. (2009b). Modeling multivariate effect sizes with structural equation models. Structural Equation Modeling, 17(3), 481 - 509.
Cheung, M.W.L. (2010). Fixed-effects meta-analyses as multiple-group structural equation models. Structural Equation Modeling, 17, 481 -509.
Colquitt, J. A., LePine, J. A., & Noe, R. A. (2000). Toward an integrative theory of training motivation: A meta-analytic path analysis of 20 years of research. Journal of Applied Psychology, 85, 678 –707.
Cudeck, R. (1989), "Analysis of Correlation Matrices Using Covariance Structure Models," Psychological Bulletin, 105(2), 317 - 327.
Furlow, C.F., & Beretvas, S.N. (2005). Meta-analytic methods of pooling correlation matrices for structural equation modeling under different patterns of missing data. Psychological Methods, 10, 227 - 254.
Generalized Least Square (n.d.).In Wikipedia. (Online) Retrieved from : http://en.wikipedia.org/wiki/Generalized_least_squares. [2015, March 24].
Glass, G. V., MacGaw, B., & Smith, M. L. (1984). Meta - analysis in social research. Beverly Hills, CA. : Sage.
Hafdahl, A.R. (2001). Multivariate meta-analysis for exploratory factor analytic research. Unpublished doctoral dissertation, University of North Carolina at Chapel Hill.
Hedges, L. & Olkin, I. (1985). Statistical models for meta-analysis. New York : Academic Press.
Hom, P.W., Caranikas-Walker, F., Prussia, G.E., & Griffeth, R.W. (1992). A meta-analytical structural equations analysis of a model of employee turnover. Journal of Applied Psychology, 77(6), 890.
Hunter, J. E. (1983). A causal analysis of cognitive ability, job knowledge, job performance, and supervisor ratings. In F. Landy, S. Zedeck, and J. Cleveland (Eds.), Performance measurement and theory. Hillsdale, NJ : Erlbaum. 257 – 266.
Hunter, J. E., Schmidt, F. L., & Jackson, G. B. (1982). Meta-analysis: Cumulating research findings across studies, 4.
Hunter, J.E., & Schmidt, F.L. (1990). Methods of meta–analysis: Correcting error and bias in research findings. Newbury Park, CA : Sage.
Hunter, J.E. & Schmidt, F.L. (2004). Methods of meta-analysis: Correcting error and bias in research findings. (2nded.). Thousand Oaks, CA : Sage.
Jöreskog, K.G. & Sörbom, D. (1996). LISREL 8 user's reference guide. Scientific Software International.
Mullen, B. (1989). Advance BASIC meta - analysis. Hillsdale, NJ : Erlbaum.
Premack, S. L. & Hunter, J. E. (1988). Individual unionization decisions. Psychological Bulletin, 103(2), 223.
Rosenthal, R. (1991). Essentials of behavioral research: Methods and data analysis. Mc Graw - Hill Humanities Social.
Schmidt, F. L. Hunter, J. E., & Outerbridge, A. N. (1986). Impact of job experience and ability on job knowledge, work sample performance, and supervisory ratings of job performance. Journal of applied psychology, 71(3), 432.
Silver, N.C. & Dunlap, W.P. (1987). Averaging correlation coefficients: should Fisher's z transformation be used? Journal of Applied Psychology, 72(1), 146.
Slavin, R. E. (1986). Best-evidence synthesis: An alternative to meta-analytic and traditional reviews. Educational researcher, 15(9), 5 - 11.
Tangutairuang, T. (2015). Meta-Analysis SEM in Leadership. (Online) Retrieved from : http://www.slideshare.net/twatchait/meta-analysisseminleadership. [2015, May 20].
Tett, R. P. & Meyer, J. P. (1993). Job satisfaction, organizational commitment, turnover intention, and turnover: Path analyses based on meta-analytic findings. Personnel Psychology, 46, 259 – 290.
Viswesvaran, C. & Ones, D.S. (1995). Theory testing: combining psychometric meta - analysis and structural equations modeling. Personnel Psychology, 48(4), 865 - 885.
Wilson, D.B. (2015). Meta - analysis macros for SAS, SPSS, and Stata. (Online) Retrieved from : http://mason.gmu.edu/~dwilsonb/ma.html. [2015, May 3].
Wiratchai, N. & Wongwanich, S. (1998). Educational Research Synthesis with Meta-Analysis and Content Analysis. The Office of Education Commission, Bangkok, Thailand. (in Thai)