Zum Inhalt

Im Erscheinen

  • Stadler, M., Doebler, P., Mertins, B. & Delucchi Danhier, R. (accepted). Statistical Modeling of Dynamic Eye Tracking Experiments: Relative Importance of Visual Stimulus Elements for Gaze Behavior in the Multi-Group Case. Behavior Research Methods. [DOI].
  • Welz, T., Doebler, P. & Pauly, M. (accepted). Fisher transformation based Confidence Intervals of Correlations in Fixed- and Random-Effects Meta-Analysis. British Journal of Mathematical and Statistical Psychology. [DOI].
  • Doebler, A. & Doebler, P. (online first). Rotate and Project: Measurement of the Intended Concept with Unidimensional Item Response Theory from Multidimensional Ordinal Items. Multivariate Behavioral Research, 17 pages. [DOI].
  • Gühne, D., Condon, D. M., Luo, F., Sun, L. & Doebler, P. (online first). Validity and reliability of automatically generated propositional reasoning items: A multilingual study of the challenges of verbal item generation. European Journal of Psychological Assessment. [DOI].
  • Dworak, E. M., Revelle, W., Doebler, P. & Condon, D. M. (accepted). Using the International Cognitive Ability Resource as an open source tool to explore individual differences in cognitive ability. Personality and Individual Differences.
  • Interests, Motives and Psychological Burdens in Times of Crisis and Lockdown: Google Trends as Information Source for Policy Makers. (accepted). Journal of Medical Internet Research. [DOI].




  • Doebler, P., Doebler, A., Buczak, P., & Groll, A. (2020). Interactions of Genetic and Environment Scores: Alternating Lasso Regularization Avoids Overfitting and Finds Interpretable Scores. [DOI].


  • Forthmann, B. & Doebler, P. (2021). Reliability of Researcher Capacity Estimates and Count Data Dispersion: A Comparison of Poisson, Negative Binomial, and Conway-Maxwell Poisson Models. Scientometrics, 126, 3337–3354. [DOI].
  • DeVries, J. M., Szardenings, C., Doebler, P. & Gebhardt, M. (2021). Subject-Specific Self-Concept and Global Self-Esteem Mediate Risk Factors for Lower Competency in Mathematics and Reading. Social Sciences, 10(1), 11p. [DOI].
  • Olderbak, S., Riggenmann, O., Wilhelm, O., & Doebler, P. (2021). Reliability generalization of tasks and recommendations for assessing the ability to perceive facial expressions of emotion. Psychological Assessment. Advance online publication. [DOI].


  • Forthmann, B., Gühne, D. & Doebler, P. (2020). Revisiting Dispersion in Count Data Item Response Theory Models: The Conway-Maxwell-Poisson Counts Model. British Journal of Mathematical and Statistical Psychology, 73(S1), 32–50. [DOI].
  • Beisemann, M., Doebler, P. & Holling, H. (2020). Comparison of random-effects metaanalysis models for the relative risk in the case of rare events: A simulation study. Biometrical Journal, 62(7), 1597–1630. [DOI].
  • Beisemann, M.,Wartlick, O. & Doebler, P. (2020). Comparison of Recent Acceleration Techniques for the EM algorithm in One-and Two-Parameter Logistic IRT models. Psych, 2(4), 209–252. [DOI]
  • Ravand, H., Baghaei, P. & Doebler, P. (2020). Examining Parameter Invariance in a General Diagnostic Classification Model. Frontiers in Psychology, 10, 10 p. [DOI].
  • Büscher, R., Beisemann, M., Doebler, P., Steubl, L., Domhardt, M., Cuijpers, P., Kerkhof, A. & Sander, L. B. (2020). Effectiveness of Internet- and Mobile-Based Cognitive Behavioral Therapy to Reduce Suicidal Ideation and Behaviours: Protocol for a Systematic Review and Meta-Analysis of Individual Participant Data. International Journal of Environmental Research and Public Health, 17(14), 11p. [DOI].
  • Domhardt, M., Letsch, J., Kybelka, J., Königsbauer, J., Doebler, P. & Baumeister, H. (2020). Are Internet- and mobile-based interventions effective in adults with diagnosed panic disorder and/or agoraphobia? A systematic review and meta-analysis. Journal of Affective Disorders, 276, 169–182. [DOI].
  • DeVries, J. M., Szardenings, C., Doebler, P. & Gebhardt, M. (2020). Individualized Assignments, Group Work and Discussions: How They InteractWith Class Size, Low Socioeconomic Status, and Second Language Learners. Frontiers in Education, 5(65), 13p. [DOI].
  • Forthmann, B., Grothjahn, R., Doebler, P. & Baghaei, P. (2020). A Comparison of Different Item Response Theory Models for Scaling Speeded C-Tests. Journal of Psychoeducational Assessment, 38. [DOI].
  • Rupp, C., Gühne, D., Falke, C., Doebler, P., Andor, F. & Buhlmann, U. (2020). Comparing effects of detached mindfulness and cognitive restructuring in obsessivecompulsive disorder using ecological momentary assessment. Clinical Psychology & Psychotherapy, 27, 193–202. [DOI].
  • Nelson, J., Klumparendt, A., Doebler, P. & Ehring, T. (2020). Everyday Emotional Dynamics in Major Depression. Emotion, 20(2), 179–191. [DOI].


  • Baghaei, P. & Doebler, P. (2019). Introduction to the Rasch Poisson Counts Model: An R Tutorial. Psychological Reports, 122(5). [DOI].
  • Rupp, C., Jürgens, C., G¨uhne, D., Doebler, P., Andor, F. & Buhlmann, U. (2019). A study on treatment sensitivity of ecological momentary assessment in obsessive-compulsive disorder. ClinicalPsychology&Psychotherapy, 26, 695– 706. [DOI].
  • Rupp, C., Jürgens, C., Doebler, P., Andor, F. & Buhlmann, U. (2019). A randomized waitlist-controlled trial comparing detached mindfulness and cognitive restructuring in obsessive-compulsive disorder. PLoS ONE, 14(3), e0213895. [DOI].
  • Jürgens,C.,Rupp,C.,Doebler,P.,Andor,F.&Buhlmann,U.(2019).Metacognitionin obsessive-compulsive disorder symptom dimensions: Role of fusion beliefs, beliefs about rituals and stop signals. Journal of Obsessive-Compulsive and Related Disorders, 21, 102–111. [DOI].
  • Olderbak, S., Semmler, M. & Doebler, P. (2019). Four-Branch Model of Ability Emotional Intelligence with Fluidand Crystallized Intelligence:AMeta-Analysis of Relations. Emotion Review, 11(2), 166–183. [DOI].
  • Forthmann, B., Wilken, A., Doebler, P. & Holling, H. (2019). Strategy Induction Enhances Creativity in Figural Divergent Thinking. Journal of Creative Behavior, 53(1), 18–29. [DOI].
  • Doebler, P., Brunn, G. & Freise, F. (2019). Das Unnmessbare messen: Statistik, Intelligenz und Bildung. In W. Krämer & C. Weihs (Hrsg.), Faszination Statistik (S. 170–176). Berlin, Springer.


  • Hartung, J., Doebler, P., Schroeders, U. & Wilhelm, O. (2018). Dedifferentiation and Differentiation of Intelligence in Adults Across Age and Years of Education. Intelligence, 69, 37–49. [DOI].
  • Loe, B. S., Sun, L., Simonfy, F. & Doebler, P. (2018). Evaluating an Automated Number Series Item Generator Using Linear Logistic Test Models. Journal of Intelligence, 6(20), 25p. [DOI].
  • Doebler, P., Bürkner, P.-C. & R¨ucker, G. (2018). Statistical Packages for Diagnostic Meta-Analysis and Their Application. In DiagnosticMeta-Analysis: A Useful Tool for Clinical Decision-Making (S. 161–181). New York, Springer.


  • Bürkner, P.-C., Doebler, P. & Holling, H. (2017). Optimal design of the Wilcoxon-Mann-Whitney-test. Biometrical Journal, 59 (1), 25–40. [DOI].
  • Königbauer, J., Letsch, J., Doebler, P., Ebert, D. & Baumeister, H. (2017). Internet-and Mobile-based Depression Interventions for People with Diagnosed Depression: A Systematic Review and Meta-analysis. Journal of Affective Disorders,223, 28–40. doi:10.1016/j.jad.2017.07.021.
  • Kröll, C., Doebler, P., & Nüesch, S. (2017). Meta-analytic evidence of the effectiveness of stress management at work. European Journal of Work and Organizational Psychology, 26, 677--693. [DOI]
  • Nelson, J., Klumparendt, A., Doebler, P. & Ehring, T. (2017). Childhood maltreatment and characteristics of adult depression: a meta-analysis. British Journal of Psychiatry. 210, 96–104. [DOI]
  • Rupp, C., Doebler, P., Ehring, T. & Voßbeck-Elsebusch, A. (2017). Emotional Processing Theory put to test: A meta-analysis on the association between process and outcome measures in exposure therapy. Clinical Psychology & Psychotherapy, 24 (3), 697–711. doi:10.1002/cpp.2039.
  • Schwenk, C., Kuhn, J., Gühne, D., Doebler, P. & Holling, H. (2017). Auf Goldmünzenjagd: Psychometrische Kennwerte verschiedener Scoringansätze bei computergestützter Lernverlaufsdiagnostik im Bereich Mathematik. Empirische Sonderpädagogik, 2, 123–142.
  • Schwenk, C., Sasanguie, D., Kuhn, J.-T., Kempe, S., Doebler, P., & Holling, H. (2017). (Non-)symbolic magnitude processing in children with mathematical difficulties: a meta-analysis. Research in Developmental Disabilities.64, 152–167 [DOI]


  • Doebler, P. & Scheffler, B. (2016). The relationship of choice reaction time variability and intelligence: a meta-analysis. Learning and Individual Differences, 52, 157–166. [DOI]


  • Alavash, M., Doebler, P., Holling, H., Thiel, C. & Giessing, C. (2015). Is functional integration of resting state brain networks an unspecific biomarker for working memory performance? NeuroImage, 108, 182–193. [DOI]
  • Biehler, M., Holling, H. & Doebler, P. (2015). Saddlepoint approximations of the distribution of the person parameter in the two parameter logistic model. Psychometrika, 80, 665–688. [DOI]
  • Doebler, P., Alavash, M. & Giessing, C. (2015). Adaptive experiments with a multi-variate Elo-type algorithm. Behavior Research Methods, 47 (2), 384–394. [DOI]
  • Doebler, P. & Holling, H. (2015). Meta-analysis of diagnostic accuracy and ROC curves with covariate adjusted semiparametric mixtures. Psychometrika, 80, 1084–1104. [DOI]


  • Bürkner, P. C. & Doebler, P. (2014). Testing for publication bias in diagnostic meta-analysis: a simulation study. Statistics in Medicine, 33, 3061–3077. [DOI]
  • Doebler, A., Doebler, P. & Holling, H. (2014). A latent ability model for count data and an application to processing speed. Applied Psychological Measurement, 38, 587–598. [DOI]


  • Doebler, A., Doebler, P. & Holling, H. (2013). Optimal and most exact confidence intervals for person parameters in item response theory models. Psychometrika, 78 (1), 98–115. [DOI]
  • Doebler, P. (2013). Rado’s conjecture implies that all stationary set preserving forcings are semiproper. Journal of Mathematical Logic, 13 (1), 8 pages. [DOI]
  • Doebler, P. & Schindler, R. (2013). The extender algebra and vagaries of Σ2 absoluteness. Münster Journal of Mathematics, 6 (1), 117–166.


  • Doebler, P., Holling, H. & Böhning, D. (2012). A mixed model approach to meta-analysis of diagnostic studies with binary test outcome. Psychological Methods, 17 (3), 418–436. [DOI]


  • Doebler, P. & Schindler, R. (2009). Π2 consequences of BMM + NSω1 is precipitous and the semiproperness of stationary set preserving forcings. Mathematical Research Letters, 16 (5), 797–815.


Anfahrt & Lageplan

Der Campus der Technischen Universität Dortmund liegt in der Nähe des Autobahnkreuzes Dortmund West, wo die Sauerlandlinie A45 den Ruhrschnellweg B1/A40 kreuzt. Die Abfahrt Dortmund-Eichlinghofen auf der A45 führt zum Campus Süd, die Abfahrt Dortmund-Dorstfeld auf der A40 zum Campus-Nord. An beiden Ausfahrten ist die Universität ausgeschildert.

Direkt auf dem Campus Nord befindet sich die S-Bahn-Station „Dortmund Universität“. Von dort fährt die S-Bahn-Linie S1 im 15- oder 30-Minuten-Takt zum Hauptbahnhof Dortmund und in der Gegenrichtung zum Hauptbahnhof Düsseldorf über Bochum, Essen und Duisburg. Außerdem ist die Universität mit den Buslinien 445, 447 und 462 zu erreichen. Eine Fahrplanauskunft findet sich auf der Homepage des Verkehrsverbundes Rhein-Ruhr, außerdem bieten die DSW21 einen interaktiven Liniennetzplan an.

Zu den Wahrzeichen der TU Dortmund gehört die H-Bahn. Linie 1 verkehrt im 10-Minuten-Takt zwischen Dortmund Eichlinghofen und dem Technologiezentrum über Campus Süd und Dortmund Universität S, Linie 2 pendelt im 5-Minuten-Takt zwischen Campus Nord und Campus Süd. Diese Strecke legt sie in zwei Minuten zurück.

Vom Flughafen Dortmund aus gelangt man mit dem AirportExpress innerhalb von gut 20 Minuten zum Dortmunder Hauptbahnhof und von dort mit der S-Bahn zur Universität. Ein größeres Angebot an internationalen Flugverbindungen bietet der etwa 60 Kilometer entfernte Flughafen Düsseldorf, der direkt mit der S-Bahn vom Bahnhof der Universität zu erreichen ist.