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.

Cinar, O., Umbanhowar, J., Hoeksema, J. D., & Viechtbauer, W. (2021). Using information-theoretic approaches for model selection in meta-analysis. Research Synthesis Methods, 12(4), 537-556. https://doi.org/10.1002/jrsm.1489

Rubio-Aparicio, M., López-López, J. A., Viechtbauer, W., Marín-Martínez, F., Botella, J., & Sánchez-Meca, J. (2020). Testing categorical moderators in mixed-effects meta-analysis in the presence of heteroscedasticity. Journal of Experimental Education, 88(2), 288-310. https://doi.org/10.1080/00220973.2018.1561404

Senior, A. M., Viechtbauer, W., & Nakagawa, S. (2020). Revisiting and expanding the meta-analysis of variation: The log coefficient of variation ratio. Research Synthesis Methods, 11(4), 553-567. https://doi.org/10.1002/jrsm.1423

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. https://doi.org/10.1002/jrsm.1316

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. https://doi.org/10.1002/jrsm.1336

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. https://doi.org/10.1002/sim.7588

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. https://doi.org/10.1002/jrsm.1218

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. https://doi.org/10.1186/s12874-016-0184-5

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. https://doi.org/10.1037/met0000023

Crutzen, R., Viechtbauer, W., Spigt, M., & Kotz, D. (2015). Differential attrition in health behaviour change trials: A systematic review and meta-analysis. Psychology & Health, 30(1), 122-134. https://doi.org/10.1080/08870446.2014.953526

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. https://doi.org/10.1186/1471-2288-14-103

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. https://doi.org/10.1111/bmsp.12002

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. https://doi.org/10.1016/j.jclinepi.2013.03.019

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. https://doi.org/10.1016/j.jclinepi.2010.04.004

Viechtbauer, W., & Cheung, M. W.-L. (2010). Outlier and influence diagnostics for meta-analysis. Research Synthesis Methods, 1(2), 112-125. https://doi.org/10.1002/jrsm.11

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1-48. https://doi.org/10.18637/jss.v036.i03

van Amelsvoort, L. G., Viechtbauer, W., & Spigt, M. G. (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. https://doi.org/10.1016/j.jclinepi.2008.08.011

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. https://doi.org/10.4135/9781412995627.d37

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). Book review of "Publication bias in meta-analysis: Prevention, assessment and adjustments". Psychometrika, 72(2), 269-271. https://doi.org/10.1007/s11336-006-1450-y

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. https://doi.org/10.3102/1076998606298034

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. https://doi.org/10.1027/0044-3409.215.2.104

Viechtbauer, W. (2007). Confidence intervals for the amount of heterogeneity in meta-analysis. Statistics in Medicine, 26(1), 37-52. https://doi.org/10.1002/sim.2514

Viechtbauer, W. (2007). Hypothesis tests for population heterogeneity in meta-analysis. British Journal of Mathematical and Statistical Psychology, 60(1), 29-60. https://doi.org/10.1348/000711005X64042

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. https://doi.org/10.1016/S1475-9144(05)04019-1

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. https://doi.org/10.3102/10769986030003261

articles.txt · Last modified: 2021/09/09 09:19 by Wolfgang Viechtbauer

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