Wolfgang Viechtbauer

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Below, you can find PDFs of a selection of my publications with focus on my more methodological/statistical research, especially with respect to meta-analysis and mixed-effects models in general. You can find more PDFs of many of my articles on the Maastricht University Research Publications repository. If you cannot find an article there, feel free to email me in case you don't have access and I would be happy to send you a copy.

Viechtbauer, W. (in press). Statistical methods for ESM data. In I. Myin-Germeys & P. Kuppens (Eds.), The open handbook of Experience Sampling Methodology: A step-by-step guide to designing, conducting, and analyzing ESM studies.

Viechtbauer, W. (2021). Model checking in meta-analysis. In C. H. Schmid, T. Stijnen, & I. R. White (Eds.), Handbook of meta-analysis (pp. 219-254). Boca Raton, FL: CRC Press.

Langan, D., Higgins, J. P. T., Jackson, D., Bowden, J., Veroniki, A. A., Kontopantelis, E., Viechtbauer, W., & Simmonds, M. (2019). A comparison of heterogeneity variance estimators in simulated random-effects meta-analyses. Research Synthesis Methods, 10(1), 83-98.

van Aert, R. C. M., van Assen, M. A. L. M., & Viechtbauer, W. (2019). Statistical properties of methods based on the Q-statistic for constructing a confidence interval for the between-study variance in meta-analysis. Research Synthesis Methods, 10(2), 225-239.

Jackson, D., Law, M., Stijnen, T., Viechtbauer, W., & White, I. R. (2018). A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio. Statistics in Medicine, 37(7), 1059-1085.

Jacobs, P., & Viechtbauer, W. (2017). Estimation of the biserial correlation and its sampling variance for use in meta-analysis. Research Synthesis Methods, 8(2), 161-180.

Law, M., Jackson, D., Turner, R., Rhodes, K., & Viechtbauer, W. (2016). Two new methods to fit models for network meta-analysis with random inconsistency effects. BMC Medical Research Methodology, 16, 87.

Viechtbauer, W., López-López, J. A., Sánchez-Meca, J., & Marín-Martínez, F. (2015). A comparison of procedures to test for moderators in mixed-effects meta-regression models. Psychological Methods, 20(3), 360–374.

Crutzen, R., Viechtbauer, W., Spigt, M., & Kotz, D. (2015). Differential attrition in health behaviour change trials: A systematic review and meta-analysis. Psychology and Health, 30(1), 122-134.

Jackson, D., Turner, R., Rhodes, K., & Viechtbauer, W. (2014). Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models. BMC Medical Research Methodology, 14(103).

López-López, J. A., Marín-Martínez, F., Sánchez-Meca, J., Van den Noortgate, W., & Viechtbauer, W. (2014). Estimation of the predictive power of the model in mixed-effects meta-regression: A simulation study. British Journal of Mathematical and Statistical Psychology, 67(1), 30-48.

Crutzen, R., Viechtbauer, W., Kotz, D., & Spigt, M. (2013). No differential attrition was found in randomized controlled trials published in general medical journals: A meta-analysis. Journal of Clinical Epidemiology, 66(9), 948-954.

Viechtbauer, W. (2010). Meta-analyse. In H. Holling & B. Schmitz (Eds.), Handbuch Statistik, Methoden und Evaluation (pp. 743-756). Göttingen, Germany: Hogrefe.

Viechtbauer, W. (2010). Learning from the past: Refining the way we study treatments. Journal of Clinical Epidemiology, 63(9), 980-982.

Viechtbauer, W., & Cheung, M. W.-L. (2010). Outlier and influence diagnostics for meta-analysis. Research Synthesis Methods, 1(2), 112-125.

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1-48. URL: http://www.jstatsoft.org/v36/i03/.

van Amelsvoort, L. G. P. M., Viechtbauer, W., & Spigt, M. (2009). Spuriously precise results from meta-analysis: Is better statistical correction or a more critical methodological assessment warranted? Journal of Clinical Epidemiology, 62(2), 123-125.

Viechtbauer, W. (2008). Analysis of moderator effects in meta-analysis. In J. Osborne (Ed.), Best practices in quantitative methods (pp. 471-487). Thousand Oaks, CA: Sage.

Roberts, B. W., Kuncel, N. R., Viechtbauer, W., & Bogg, T. (2007). Meta-analysis in personality psychology: A primer. In R. W. Robins, R. C. Fraley, & R. F. Krueger (Eds.), Handbook of research methods in personality psychology (pp. 652-672). New York: Guilford Press.

Viechtbauer, W. (2007). Review of 'Publication bias in meta-analysis: Prevention, assessment and adjustment' by Hannah R. Rothstein, Alexander J. Sutton, and Michael Borenstein (Eds). Psychometrika, 72(2), 269-271.

Viechtbauer, W. (2007). Approximate confidence intervals for standardized effect sizes in the two-independent and two-dependent samples design. Journal of Educational and Behavioral Statistics, 32(1), 39-60.

Viechtbauer, W. (2007). Accounting for heterogeneity via random-effects models and moderator analyses in meta-analysis. Zeitschrift für Psychologie (Journal of Psychology), 215(2), 104-121.

Viechtbauer, W. (2007). Confidence intervals for the amount of heterogeneity in meta-analysis. Statistics in Medicine, 26(1), 37-52.

Viechtbauer, W. (2007). Hypothesis tests for population heterogeneity in meta-analysis. British Journal of Mathematical and Statistical Psychology, 60(1), 29-60.

Viechtbauer, W., & Budescu, D. (2005). A model selection approach to testing dependent ICCs. In F. Dansereau & F. Yammarino (Eds.), Multi-level issues in strategy and research methods: Vol. 4. Research in multi-level issues (pp. 433-454). Amsterdam: JAI Press/Elsevier.

Viechtbauer, W. (2005). Bias and efficiency of meta-analytic variance estimators in the random-effects model. Journal of Educational and Behavioral Statistics, 30(3), 261-293.

articles.txt · Last modified: 2021/06/09 14:44 by Wolfgang Viechtbauer

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