Çok Düzeyli Meta-Analiz Yöntemleri Üzerine Bir Çalışma

Year 2016, Volume: 7 Issue: 1, 1 - 17, 30.06.2016

Sedat Şen , Nihal Akbaş

https://doi.org/10.21031/epod.29995

Cited By: 6

Abstract

Bu çalışmada meta-analiz alanyazınında kullanılan istatistiksel modeller incelenmiştir. Özellikle alanyazında karşılaşılan bağımlılık problemini çözmek için önerilen yöntemlerden birisi olan çok düzeyli meta-analiz modellerinin tanıtılması amaçlanmıştır. Çalışmada ilk olarak geleneksel meta-analiz modellerinin nasıl yapıldığından, daha sonra meta-analizde kullanılan yeni yaklaşımlardan ve çok düzeyli meta-analiz modellerinden bahsedilmiştir. Bu çalışmada daha önce geleneksel meta-analiz modelleriyle analiz edilmiş bir meta-analiz verisi geleneksel, iki düzeyli ve üç düzeyli meta-analiz modelleri ile analiz edilmiştir. Kullanılan veri özel eğitimde sıklıkla çalışılan yaratıcılık yapısı ile psikolojik bir rahatsızlık olan psikotisizm arasındaki ilişkiyi içeren çalışmalardan elde edilen etki büyüklüklerini içermektedir. Yapılan üç farklı analizde iki düzeyli meta-analiz sonuçlarının geleneksel (rastgele etkiler modeli) meta-analiz sonuçlarıyla aynı olduğu görülmüş buna ek olarak iki düzeyli modellerin üç düzeye genişletilerek bağımlılık problemini çözmek için nasıl kullanılacağı belirtilmiştir. Çalışmada Türkiye’deki araştırmacılar için meta-analiz alanyazınında geliştirilen bu yeni yöntemler hakkında bilgiler sunulmuştur.

References

• Acar, S., & Runco, M. A. (2012). Psychoticism and creativity: A meta-analytic review. Psychology of Aesthetics, Creativity and the Arts, 6, 341–350.
• Acar, S., & Sen, S. (2013). A multilevel meta-analysis of the relationship between creativity and schizotypy. Psychology of Aesthetics, Creativity and the Arts, 7, 214–228.
• Bachtold, L. M. (1980). Psychoticism and creativity. Journal of Creative Behavior, 14, 242–248.
• Bateman, I. J. & Jones, A. P. (2003). Contrasting conventional with multi-level modelling approaches to meta-analysis: Exceptation consistency in UK woodland recreation values, CSERGE Working Paper EDM, No. 03-01.
• Becker, B. J. (2000). Multivariate meta-analysis. In H. E. A. Tinsley and S. G. Brown (Eds.) Handbook of Applied Statistics and Mathematical Modeling (pp. 499-525). San Diego, CA: Academic Press.
• Begg, C. B. (1994). Publication bias. In H. Cooper & L. Hedges (Eds.), Handbook of research synthesis (pp. 399–409). New York, NY: Sage Publication.
• Bornmann, L., Mutz, R., Hug, S. E., & Daniel, H. D. (2011). A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5(3), 346– 359.
• Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models social and behavioral research: Applications and data analysis methods. Newbury Park, CA: Sage.
• Chavez-Eakle, R. A., Lara, M. C., & Cruz-Fuentes, C. (2006). Personality: A possible bridge between creativity and psychopathology? Creativity Research Journal, 18, 27–38.
• Cheung, M. W.L. (2014). Modeling dependent effect sizes with three-level meta-analyses: A structural equation modeling approach. Psychological Methods, 19, 211–229.
• Cochran, W. G. (1954). The combination of estimates from different experiments. Biometrics, 10, 101–129.
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Mahwah, NJ: Erlbaum.
• Cooper, H., & Hedges, L.V. (1994). The handbook of research synthesis.
• New York, NY: Russell Sage Foundation.
• Cox, A. J., & Leon, J. L. (1999). Negative schizotypal traits in the relation of creativity to psychopathology. Creativity Research Journal, 12, 25–36.
• de la Torre, J., Camilli, G., Vargas, S., & Vernon, R. F. (2007). Illustration of a multilevel model for meta- analysis. Measurement and Evaluation in Counseling and Development, 40, 169–180.
• Dear, K. B., & Begg, C. B. (1992). An approach for assessing publication bias prior to performing a meta- analysis. Statistical Science, 7, 237–245.
• Dinçer, S. (2013). Meta-analize giriş. Ankara: Anı Yayıncılık.
• Eysenck, H. J. (1993). Creativity and personality: Suggestions for a theory. Psychological Inquiry, 4, 147–178.
• Eysenck, H. J., & Eysenck, S. B. G. (1976). Psychoticism as a dimension of personality. London, England: Hodder & Stoughton.
• Fisher, R. A. (1932). Statistical methods for research workers (4th ed.). London: Oliver and Boyd.
• Geeraert, L., Van den Noortgate, W., Grietens, H., & Onghena, P. (2004). The effects of early prevention programs for families with young children at risk for physical child abuse and neglect. A meta- analysis. Child Maltreatment, 9, 277–291.
• Glass, G. V. (1976). Primary, secondary and meta-analysis of research. Educational Researcher, 5, 3–8.
• Glass, G. V. (1977). Integrating findings: The meta-analysis of research. Review of Research in Education, 5, 351–379.
• Gleser, L. J. & Olkin, I. (1994). Stochastically dependent effect sizes. In The handbook of research synthesis, H. Cooper and L. V. Hedges (Eds.). New York: Russell Sage Foundation.
• Goldstein, H. (1987). Multilevel models in education and social research. London, UK: Griffen.
• Greenhouse, J. B., &Iyengar, S. (1994). Sensitivity analysis and diagnostics. In The handbook of research synthesis, H. Cooper and L. V. Hedges (Eds.). New York: Russell Sage Foundation.
• Hedeker, D., & Gibbons, R. D. (2006). Longitudinal data analysis. Hoboken, NJ: Wiley.
• Hedges, L. V. (1984). Estimation of effect size under nonrandom sampling: The effects of censoring studies yielding statistically insignificant mean differences. Journal of Educational and Behavioral Statistics, 9(1), 61–85.
• Hedges, L. V. (1992). Meta-analysis. Journal of Educational Statistics, 17, 279–296.
• Hedges, L. V. (2007). Meta-analysis. In C. R. Rao & S. Sinharay (Eds.), Handbook of statistics (Vol. 26, pp. 919–953), Amsterdam, the Netherlands: Elsevier.
• Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando, FL: Academic Press.
• Hox, J. J. (2002). Multilevel analysis: Techniques and applications. Mahwah, NJ: Erlbaum.
• Hox, J. J., & de Leeuw, E. D. (2003). Multilevel models for meta-analysis. In S. P. Reise & N. Duan (Eds.), Multilevel modelling: Methodological advances, issues, and applications (pp. 90–111). Mahwah, NJ: Lawrence Erlbaum.
• Iyengar, S., & Greenhouse, J. B. (1988). Selection models and the file drawer problem. Statistical Science, 3, 109–117.
• Karasar, N. (2007). Bilimsel araştırma yöntemi: kavramlar, ilkeler, teknikler. (17. Baskı). Ankara: Nobel Yayın Dağıtım.
• Kim, J. S. (2008). Examining the effectiveness of solution-focused brief therapy: A meta-analysis. Research on Social Work Practice, 18, 107–116.
• Konstantopoulos, S. (2011). Fixed effects and variance components estimation in three-level meta-analysis? Research Synthesis Methods, 2, 61–76.
• Kreft, I., & de Leeuw, J. (1998). Introducing multilevel modeling. Thousand Oaks, CA: Sage.
• Lebuda, I., Zabelina, D. L., & Karwowski, M. (2016). Mind full of ideas: A meta-analysis of the mindfulness–creativity link. Personality and Individual Differences, 93, 22–26.
• Lipsey, M. W., & Wilson, D. (2000). Practical meta-analysis. Thousand Oaks: CA, SAGE Publications, Inc.
• Littell, J. H., Corcoran, J., & Pillai, V. (2008). Systematic reviews and meta-analysis. Oxford University Press.
• Ludwig, A. M. (1992). Creative achievement and psychopathology: Comparison among professions. American Journal of Psychotherapy, 46,330–356.
• Marín-Martínez, F., & Sánchez-Meca, J. (1999). Averaging dependent effect sizes in meta-analysis: A cautionary note about procedures. The Spanish journal of psychology, 2, 32-38.
• Marsh, H. W., Bornmann, L., Mutz, R., Daniel, H.D., & O’Mara, A. (2009). Gender effects in the peer reviews of grant proposals: A comprehensive meta-analysis comparing traditional and multilevel approaches. Review of Educational Research, 79, 1290–1326.
• Pearson, K. (1904). Report on certain enteric fever inoculations. British Medical Journal, 2, 1243–1246.
• Post, F. (1994). Creativity and psychopathology. A study of 291 worldfamous men. British Journal of Psychiatry, 165, 22–34.
• Raudenbush, S. W., Becker, B. J., & Kalaian, H. (1988). Modeling multivariate effect sizes. Psychological Bulletin, 103, 111–120.
• Raudenbush, S. W., & Bryk, A. S. (1985). Empirical Bayes meta-analysis. Journal of Educational Statistics, 10, 75–98.
• Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd ed.). London, UK: Sage.
• Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86, 638– 641.
• Rosenthal, R. (1994). Parametric measures of effect size. In H. Cooper & L. V. Hedges (Eds.), Handbook of research synthesis (pp. 231–244). New York, NY: Russell Sage Foundation.
• Scammacca, N., Roberts, G., & Stuebing, K. K. (2014). Meta-analysis with complex research designs dealing with dependence from multiple measures and multiple group comparisons. Review of educational research, 84(3), 328–364.
• Silliman, N. P. (1997). Nonparametric classes of weight functions to model publication bias. Biometrika, 84(4), 909–918.
• Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis. New York: Oxford University Press.
• Snijders, T.A.B., & Bosker, R. J. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage Ltd.
• Tippett, L. H. C. (1931). The methods of statistics. London: Williams and Norgate.
• Van den Bussche, E., Van den Noortgate, & W., Reynvoet, B. (2009). Mechanisms of masked priming: A meta-analysis. Psychological Bulletin, 135, 452–477.
• Van den Noortgate, W., López-López, J. A., Marín-Martínez, F., & Sánchez-Meca, J. (2013). Three-level meta-analysis of dependent effect sizes. Behavior Research Methods, 45, 576–594.
• Verbeke, G., & Molenberghs, G. (2000). Linear mixed models for longitudinal data. New York: Springer- Verlag.
• Yeager, D. S., Fong, C. J., Lee, H. Y., & Espelage, D. L. (2015). Declines in efficacy of antibullying programs among older adolescents: A developmental theory and a threelevel meta-analysis. Journal of Applied Developmental Psychology, 37, 36–51.