Ausgewählte Publikationen

  •  Benda N., Bürkner P.-C., Freise F., Holling H., & Schwabe R. (in press). Adaptive Designs for Quantal Dose-Response Experiments with False Answers. Journal of Statistical Theory and Practice.
  • Bürkner P. C., Doebler P., & Holling H. (in press). Optimal design of the Wilcoxon-Mann-Whitney-test. Biometrical Journal.
  • Böhning, D., Rocchetti,I., Alfó, M., & Holling H. (in press). A flexible ratio regression approach for zero-truncated capture-recapture counts. Biometrics.
  • Chodura, S., Kuhn, J.-T., & Holling, H. (in press). Interventions for children with mathematical difficulties: A meta-analysis. Zeitschrift für Psychologie.
  • Forthmann, B., Wilken, A., Doebler, P., & Holling, H. (in press) Strategy induction enhances creativity in figural divergent thinking. Journal of Creative Behavior.
  • Kuhn, J.-T. (in press). Developmental dyscalculia: Causes, characteristics, and interventions (Editorial). Zeitschrift für Psychologie.
  • Kuhn, J.-T. (in press). Developmental dyscalculia: Neurobiological, cognitive, and developmental perspectives. Zeitschrift für Psychologie.
  • Kuhn, J.-T. (in press). Controlled attention and storage: An investigation of the relationship between working memory, short-term memory, scope of attention, and intelligence in children. Learning and Individual Differences.
  • Kuhn, J.-T., Ise, E., Raddatz, J., Schwenk, C., & Dobel, C. (in press). Basic numerical processing, calculation, and working memory in children with dyscalculia and/or ADHD symptoms. Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie.
  • Masoudi, E., Holling, H., & Wong, W. K.  (in press). Application of imperialist competitive algorithm to find minimax and standardized maximin optimal designs. Computational Statistics & Data Analysis. online available
  • Ranger, J., Kuhn, J.-.T., & Gaviria, J.-L. (in press). A race model for responses and response times in tests. Psychometrika.
  • Ranger, J., & Kuhn, J.-T. (in press). An accumulator model for responses and response times in test based on the proportional hazards model. British Journal of Mathematical and Statistical Psychology.
  •  Blum, D., Holling, H., Galibert, M. S., & Forthmann, B. (2016). Task difficulty prediction of figural analogies. Intelligence, 56, 72-81. doi: 10.1016/j.intell.2016.03.001
  • Çelik, P., Storme, M., & Forthmann, B. (2016). A new perspective on the link between multiculturalism and creativity: The relationship between core value diversity and divergent thinking. Learning and Individual Differences. doi: 10.1016/j.lindif.2016.02.002
  • Graßhoff, U., Holling, H., & Schwabe,R. (2016). Optimal Desingn for the Rasch Poisson-Gamma Model. In Kunert, J., Müller,C., Atkinson, A. (Eds.). Advances in Model-Oriented Desing and Analysis. 133-141.
  • Forthmann, B., Gerwig, A., Holling, H., Celik, P., Storme, M., & Lubart, T. (2016). The Be-Creative Effect in Divergent Thinking: The Interplay of Instructions and Objekt Frequency. Intelligence, 57, 25-32. doi: 10.1016/j.intell.2016.03.005
  • Holling, H., & Schwabe, R. (2016). Statistical Optimal Design Theory. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of Item Response Theory (Vol 2), 313-339.
  • Raddatz, J., Kuhn, J.-T., Holling, H., Moll, K., & Dobel,C. (2016). Comorbidity of arithmetic and reading disorder: Basic number processing and calculation in children with learning inpairments. Journal of Learning Disabilities. 
  • Alavash, M., Doebler, P., Holling, H., Thiel, C. M., & Gießing, C. (2015). Is functional integration of resting state brain networks an unspecific biomarker für working memory performance? NeuroImage, 108, 182-193.
  • Biehler M., Doebler P., & Holling H. (2015). Saddlepoint approximations of the distribution of the person parameter in the two parameter logistic model. Psychometrika, 665-688.
  • Doebler, P., & Holling, H. (2015). Meta-analysis of diagnostic accuracy and ROC curves with covariate adjusted semiparametric mixtures. Psychometrika, 1084-1104.
  • Graßhoff, U., Holling, H., & Schwabe, R. (2015). Poisson model with three binary predictors: When are saturated designs optimal? (Stocastic Models, Statistics and Their Applications). In A. Steland, E. Rafajlowicz & K. Szajkowski (Eds.), Stochastic Models, Statistics and Their Applications. (pp.75-82).Cham: Springer.
  • Holling. H., Böhning, W., & Böhning, D. (2015). The covariate-adjusted frequency plot for the Rasch Poisson counts model. Thailand Statistician, 67-78.
  • Ranger, J., & Kuhn, J.-T. (2015). Assessing person fit with the information matrix test. Methodology, 11, 3-12.
  • Ranger, J., & Kuhn, J.-T. (2015). Modeling information accumulation in psychological tests using item response times. Journal of Educational and Behavioral Statistics, 40, 274-306. 
  • Bürkner, P.C., & Doebler, P. (2014). Testing for Publication Bias in Diagnostic Meta-Analysis: A simulation Study. Statistics in Medicine.
  • Charoensawat, S., Böhning, W., Böhning, D., & Holling, H. (2014). Meta-analysis and meta-modelling for diagnostic problems. BMC Medical Research Methodolody, 14-56.
  • Doebler, P., Doebler, A., & Holling, H. (2014). A latent ability model for count data and an application to processing speed. Applied Psychological Measurement, 38, 587-598.
  • Kuhn, J.-T., & Holling H. (2014). Number Sense or working memory? The effect of two computer-based trainings on mathematical skills in elementary school. Advances in Cognitive Psychology, 10, 59-67. 
  • Doebler P. (2013). Rado’s Conjecture implies that all stationary set preserving forcings are semiproper. Journal of Mathematical Logic, 13(1), 8 pages.
  • Doebler, A., Doebler, P., & Holling, H. (2013). Optimal and Most Exact Con
    dence Intervals for Person Parameters in Item Response Theory Models.     Psychometrika, 78(1), 98-115.
  • Doebler P., & Schindler R. (2013). The extender algebra and vagaries of Σ12 absoluteness. Münster Journal of Mathematics, 6, 117-166.
  • Graßhoff U., Holling, H., & Schwabe, R. (2013). Optimal design for count data with binary predictors in item response theory. Advances in Model-Oriented Designs and Analysis, 117-124.
  • Graßhoff, U., Holling, H., & Schwabe, R. (2013). Optimal design for count data with binary predictors in item response theory. In D. Ucinski, A. C. Atkinson & M. Patan (Eds.) 10-Adcances in Model-Oriented Design and Analysis. (pp. 117-124). Heidelberg: Physica.
  • Holling, H., Böhning, W., Böhning, D., & Formann, A. K. (2013). The Covariate-Adjusted Frequency Plot. Statistical Methods in Medical Research.
  • Holling, H. & Schwabe, R. (2013) An introduction to optimal design. Zeitschrift für Psychologie, 221, 3, S. 124-144.
  • Kuhn, J.-T. & Kiefer, T. (2013). Optimal test assembly in practice: The design of the Austrian educational standards assessment in mathematics. Zeitschrift für Psychologie, 221, 190-200.
  • Kuhn, J.-T., Raddatz, J., Holling, H., & Dobel, C. (2013). Dyskalkulie vs. Rechenschwäche: Basisnumerische Verarbeitung in der Grundschule. Lernen und Lernstörungen, 2, 229-247.
  • Ranger, J., & Kuhn, J.-T. (2013). Analyzing response times in tests with rank correlation approaches. Journal of Educational and Behavioral Statistics, 38, 61-80.
  • Skodzik, T., Holling, H., & Pedersen, A. (2013). Long-term memory performance in adult ADHD - a Meta-Analysis. Journal of Attention Disorders. Online publication. 
  • Doebler, A. (2012). The Problem of Bias in Person Parameter Estimation in Adaptive Testing. Applied Psychological Measurement, 36(4), 255-270.
  • Doebler, P., Holling, H., & Böhning, D. (2012). A Mixed Model Approach to Meta-Analysis of Dignostic Studies with Binary Test Outcome. Psychological Methods, 17, 418-436.
  • Graßhoff, U., Doebler, A., Holling, H., & Schwabe, R. (2012). Optimal design for linear regression models in the presence of heteroscedasticity caused by rendom coefficients. Journal of Statistical Planning and Inference 142, 1108-1113.
  • Graßhoff, U., Großmann, H., Holling, H., & Schwabe, R. (2012). Optimal Design for Descrete Choice Experiments. Journal of Statistical Planning and Inference 143, 167-175.
  • Graßhoff, U., Holling, H., & Schwabe, R. (2012). Optimal design for the Rasch model. Psychometrika 77, 710-723.
  • Holling, H., & Böhning, W., & Böhning, D. (2012). Likelihood Based Clustering of Meta-Analytic SROC Curves. Psychometrika, 77, 106-126.
  • Holling, H., Böhning, W., & Böhning, D. (2012). Meta-analysis of diagnostic studies based upon SROC-curves: A mixed model approach using the Lehmann family. Statistical Modelling - An International Journal 12, issue 4, 347.
  • Holling, H., & Schwabe, R. (2012). Discussion of the paper Optimum design of experiments for statistical inference by Gilmour, S. G. and Trinca, L. A. Journal of the Royal Statistical Society, Series C (Applied Statistics), 61, 385.
  • Niwitpong, S., Böhning, D., van der Heijden, P. G. H., & Holling, H. (2012). Capture-Recapture Estimation Based Upon the Geometric Distribution allowing for Heterogenity. Metrika.
  • Ranger, J., & Kuhn, J.-T. (2012). Assessing fit of item response models using the information matrix test. Journal of Educational Measurement, 49, 247-268.
  • Ranger, J., & Kuhn, J.-T. (2012). A flexible latent trait model for response times in tests. Psychometrika, 77, 31-47.
  • Ranger, J., & Kuhn, J.-T. (2012). Improving IRT model calibration by considering response times in psychological tests. Applied Psychological Measurement, 36, 214-131.
  • Ranger, J., & Kuhn, J.-T. (2012). A flexible latent trait model for response times in tests. Psychometrika, 77, 31-47. 
  • Böhning, D., Holling, H., & Pantilea, V. (2011). A limitation of the diagnostic-odds ratio in determining an optimal cut-off value for a continuous diagnostic test. Statistical Methods in Medical Research, 20, 541-550.
  • Freund, P. A. & Holling, H. (2011). Who wants to take an intelligence test? Personality and achievement motivation in the context of ability testing. Personality and Individual Differences, 50, 723-728.
  • Freund, P. A., & Holling, H. (2011). How to get really smart: Modeling retest and training effects in ability testing using computer-generated figural matrix items. Intelligence, 39, 233-243.
  • Freund, P. A., & Holling, H. (2011). Retest effects in matrix test performance: Differential impact of predictors at different hierarchy levels in an educational setting. Learning and Individual Differences, 21, 597-601.
  • Freund, P. A., Kuhn, J.-T., & Holling, H. (2011). Measuring current achievement motivation with the QCM: Short form development and investigation of measurement invariance. Personality and Individual Differences, 51, 629-634.
  • Holling, H., & Schwabe, R. (2011). The usefulness of Bayesian optimal designs for descrete choice experimentes by Roselinde Kessels, Bradley Jones, Peter Goos and Martina Vandebroek. Applied Stochastic Models in Business and Industry, 27, 189-192.
  • Vock, M., Preckel, F., & Holling, H. (2011). Mental abilities and school achievement: A Test of a mediation hypothesis. Intelligence, 39, 357-369.
  • Zeuch, N., Holling, H., & Kuhn, J.-T. (2011). Analysis of the Latin Square Task with linear logistic test models. Learning and Individual Differences, 21, 629-632.

 

Bücher

  • Holling, H., & Gediga, G. (2015) Statistik - Testverfahren [Statistics-Tests]. Göttingen: Hogerefe.
  • Holling, H., & Gediga, G. (2013). Statistik - Wahrscheinlichkeitstheorie und Schätzverfahren. [Statistics - Probability theory and estimation methods]. Göttingen: Hogrefe.
  • Holling, H., & Gediga, G. (2011). Statistik-Deskriptive Verfahren [Descriptive statistical methods]. Göttingen: Hogrefe.