Selected publications

 

2023

Statistics

  • Freise, F., Holling, H., & Schwabe, R. (2023). Optimal design for estimating the mean ability over time in repeated item response testing. Journal of Statistical Planning and Inference, 23, 266-282.
  • Holling, H. & Jansen, K. (accepted). Using nonparametric mixture models to model effect heterogeneity in meta-analysis of very rare events. In Wiberg, M., Molenaar, D., González, & Kim, J.-S., & Hwang, H. (Eds.). Quantitative Psychology: The 87th Annual Meeting of the Psychometric Society, 2022. New York: Springer.
  • Jansen K. & Holling, H. (2022). Random‐effects meta‐analysis models for the odds ratio in the case of rare events under different data‐generating models: A simulation study. Biometrical Journal, 65:2200132

Meta-Analysis

  • Eckes, T., Buhlmann, U. , Holling, H., & Möllmann, A. (2023). Comprehensive ABA-based interventions in the treatment of children with autism spectrum disorder – a meta-analysis. BMC Psychiatry, 23:133.
  • Harenbrock, J., Forthmann, B., & Holling, H. (accepted). Reliability of Situational Judgment Tests: A Meta-analysis. Journal of Personnel Psychology.
  • Hoppen, T. H., Jehn, M., Holling, H., Mutz, J., Kip, A., & Morina, N. (accepted). The efficacy and acceptability of psychological interventions for adult PTSD: A network and pairwise meta-analysis of randomized controlled trials. Journal of Consulting and Clinical Psychology.
  • Viesel-Nordmeyer, N., Reuber, J., Kuhn, J.-K., Moll, K., Holling, H.,& Dobel, C. (accepted). Cognitive profiles of children with isolated and comorbid learning difficulties in reading and math: A meta-analysis. Educational Psychology Review.

2022

Statistics

  • Böhning, D., Sangnawakij, P., & Holling, H. (2022). Estimating risk and rate ratio in rare events meta-analysis with the Mantel–Haenszel estimator and assessing heterogeneity. The International Journal of Biostatistics.

  • Böhning, D., Sangnawakij, P., & Holling, H. (2022). Confidence interval estimation for the Mantel–Haenszel estimator of the risk ratio and risk difference in rare event meta-analysis with emphasis on the bootstrap. Journal of Statistical Computation and Simulation, 92, 1267-1291.

  • Holling, H., Jansen, J., Böhning, W., Böhning, D., & Martin, S. (2022). Estimation of effect heterogeneity in rare events meta-analysis. Psychometrika. DOI:10.1007/s11336-021-09835-5

  • Masoudi, E., Holling, H., Wong, W. K., & Seongho, K. (2022). ICAOD: An R Package for Finding Optimal Designs for Nonlinear Statistical Models by Imperialist Competitive Algorithm. The R Journal, 14/3.

Meta-Analysis

  • Badenoch, J. B., Rengasamy, E. R., Watson C. , Jansen, K. , Chakraborty, S., …, Holling, H., …, Rooney, A.G. (2022). Persistent neuropsychiatric symptoms after COVID-19: a systematic review and meta-analysis. Brain Communications, 4, 1, fcab297. DOI:10.1093/braincomms/fcab297
  • Kip, A., Diele, J., Holling, H., & Morina, N. (2022). The relationship of trauma-related guilt with PTSD symptoms in adult trauma survivors: A meta-analysis. Psychological Medicine. DOI: 10.1017/S0033291722001866 
  • Neuber, L., Englitz, C., Schulte, N., Forthmann, B., & Holling, H. (2022). How work engagement relates to performance and absenteeism: a meta-analysis. European Journal of Work and Organizational Psychology, 31, 292-315. DOI:10.1080/1359432X.2021.1953989

Assessment, Cognitive Abilities

  • Zandi, N., Karwowski, M., Forthmann, B., & Holling, H. (2022). How Stable is the Creative Self-Concept? A Latent State-Trait Analysis. Psychology of Aesthetics Creativity and the Arts.

Software

  • Masoudi, E., Holling, H., Wong, W. K. & Kim, S. (2022). Optimal Designs for Nonlinear Statistical Models by Imperialist Competitive Algorithm (ICA). Package ‘ICAOD’.  https://CRAN.R-project.org/package=ICAOD

2021

Statistics

  • Böhning, D., Sangnawakij, P., & Holling, H. (2021). Confidence interval estimation for the Mantel–Haenszel estimator of the risk ratio and risk difference in rare event meta-analysis with emphasis on the bootstrap. Journal of Statistical Computation and Simulation, 1-25. DOI:10.1080/00949655.2021.1991347
  • Böhning, D., Holling, H., Böhning, W., & Sangnawakij, P. (2021). Investigating heterogeneity in meta-analysis of studies with rare events. Metron, 79,1-14. DOI:10.1007/s40300-021-00211-y
  • Böhning, D., Martin, S., Sangnawakij, P., Jansen, K., Böhning, W. & Holling, H. (2021). Nonparametric estimation of effect heterogeneity in rare events meta-analysis: bivariate, discrete mixture model. Lobachevskii Journal of Mathematics. DOI:10.1134/S1995080221020074
  • Graßhoff, U., Großmann, H., Holling, H., & Schwabe, R. (2021). Optimal design for probit choice models with dependent utilities. Statistics, 55, 173-194. DOI:10.1080/02331888.2021.1888292
  • Sangnawakij, P., Böhning, D., & Holling, H. (2021). On the exact null-distribution of a test for homogeneity of the risk ratio in meta-analysis of studies with rare events. Journal of Statistical Computation and Simulation, 91, 420-434. DOI:10.1080/00949655.2020.1815200
  • Schulte, N., Holling, H., & Bürkner, P. (2021). Can High-Dimensional Questionnaires Resolve the Ipsativity Issue of Forced-Choice Response Formats. Educational and Psychological Measurement, 81, 262-289. DOI:10.1177/0013164420934861

Meta-Analysis

  • Gerwig, A., Miroshnik, K., Forthmann, B., Benedek, M., Karwowski, M., & Holling, H. (2021). The relationship between intelligence and divergent thinking - A meta-analytic update. Journal of Intelligence, 9, 23. DOI:10.3390/jintelligence9020023

Assessment, Cognitive Abilities

  • Kleinkorres, R., Forthmann, B., & Holling, H. (2021). An experimental approach to investigate the involvement of cognitive load in divergent thinking. Journal of Intelligence, 9, 3. DOI:10.3390/jintelligence9010003

 

2020

Statistics

  • Beisemann, M., Doebler, Ph. & Holling, H. (2020). Comparison of random-effects meta-analysis models for the relative risk in the case of rare events - A simulation study. Biometrical Journal, 62, 1597-1630. doi:10.10002/bimj.201900379
  • Böhning, D., Rocchetti, I., Maruotti, A., & Holling, H. (2020). Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods. International Journal of Infectious Diseases, 97, 197 – 201. doi.org/10.1016/j.ijid.2020.06.009
  • Freise, F., Holling, H. & Schwabe, R. (2020). Optimal designs for two-level main effects models on a restricted design region. Journal of Statistical Planning and Inference, 204, 45–54. doi:10.1016/j.jspi.2019.04.005
  • Forthmann, B., Paek, S. H., Dumas, D., Barbot, B., & Holling, H. (2020). Scrutinizing the basis of originality in divergent thinking tests: On the measurement precision of response propensity estimates. British Journal of Educational Psychology, 90, 683 – 699. doi:10.1111/bjep.12325
  • Graßhoff, U., Holling, H., Röttger, R. & Schwabe, R. (2020) Optimality regions for designs in multiple linear regression models with correlated random coefficients. Journal of Statistical Planning and Inference, 209, 267- 279. doi:10.1016/j.jspi.2020.04.004
  • Graßhoff, U., Holling, H. & Schwabe, R. (2020). D-Optimal Design for the Rasch Counts Model with Multiple Binary Predictors. British Journal of Mathematical and Statistical Psychology, 73, 541 - 555. doi.org/10.1111/bmsp.12204
  • Holling, H., Böhning, W., Masoudi, E & Sangnawakij, P. (2020). Evaluation of a new version of I² with emphasis on diagnostic problems. Communications in Statistics – Simulation and Computation, 49, 942 - 947. doi:10.1080/03610918.2018.1489553
  • Jendryczko, D., Berkemeyer, L. & Holling, H. (2020). Introducing a computerized figural memory test based on automatic item generation: An analysis with the Rasch Poisson counts model. Frontiers in Psychology, section Quantitative Psychology and Measurement. doi.org/10.3389/fpsyg.2020.00945
  • Rocchetti, I., Böhning, D., Holling, H., & Antonello Maruotti, A. (2020). Estimating the size of undetected cases of the COVID-19 outbreak in Europe: an upper bound Estimator. Epidemiologic Methods, 2020; 9(s1): 20200024. doi.org/10.1515/em-2020-002

Meta-Analysis

  • Koychev, I., Jansen, K., Dette, A., Liu, S., & Holling, H. (2020). Blood-based ATN biomarkers of Alzheimer's disease: A meta-analysis. Journal of Alzheimer's Disease. Advance online publication. DOI: 10.3233/JAD-200900
  • Kip, A., Holling, H., Priebe, S. & Morina, N. (2020). Psychological interventions for post-traumatic stress disorder and depression in refugees. A meta-analysis of randomized controlled trials. Clinical Psychology and Psychotherapy. doi:10.1002/cpp.2446
  • Landmeyer, N. C., Bürkner, P.-C., Wiendl, H., Ruck, T., Hartung, H.-P., Holling, H., Meuth, S.-G., & Johnen, A. (2020). Disease-modifying treatments and cognition in relapsing-remitting MS–a meta-analysis. Neurology. doi:10.1212/WNL.0000000000009522

Assessment, Cognitive Abilities

  • Beisemann, M., Forthmann, B., Bürkner, P. C. & Holling, H. (2020). Psychometric evaluation of an alternate scoring for the Remote Associates Test. Journal of Creative Behavior. doi:10.1002/jocb.394
  • Kleinkorres, R., Forthmann, B., & Holling, H. (in press). An Experimental Approach to Investigate the Involvement of Cognitive Load in Divergent Thinking. Journal of Intelligence.
  • Wilken, A., Forthmann, B. & Holling, H. (2020). Instructions moderate the relationship between creative perfor-mance in figural divergent thinking and reasoning capacity. Journal of Creative Behavior. doi:10.1002/jocb.392

 

2011 - 2019

Statistics

  • Bürkner P. C., Schulte N. & Holling H. (2019). On the statistical and practical limitations of Thurstonian IRT models. Educational and Psychological Measurement, 79, 827 – 854. doi:10.1177/0013164419832063
  • Masoudi, E., Holling, H., Duarte, B.P.M. & Wong, W.K. (2019). Metaheuristic Adaptive Cubature Based Algorithm to Find Bayesian Optimal Designs for Nonlinear Models. Journal of Computational and Graphical Statistics, 28, 861-876. doi:10.1080/10618600.2019.1601097
  • Sangnawakij, P., Böhning, D. Niwitpong, S., Adams, S., Stanton, M. & Holling, H. (2019). Meta-Analysis without study-specific variance information: Heterogeneity case. Statistical Methods in Medical Research, 28, 196-210. doi:10.1177/0962280217718867
  • Bürkner P. C., Schwabe S., & Holling H. (2018). Optimal Designs for the Generalized Partial Credit Model. British Journal of Mathematical and Statistical Psychology, 72, 271-293
  • Holling, H. (2018). Contribution to the discussion of “When should meta‐analysis avoid making hidden normality assumptions?” Biometrical Journal, 60, 1091-1093.
  • Sangnawakaij, P., Böhning, D. Adams, S., Stanton, M. & Holling, H. (2017). Statistical methodology for estimating the mean difference in a meta.analysis without study-specific variance information. Statistics in Medicine, 36, 1395-1413.
  • Benda N., Bürkner P.-C., Freise F., Holling, H., & Schwabe R. (2017). Adaptive Designs for Quantal Dose-Response Experiments with False Answers. Journal of Statistical Theory and Practice, 11, 361-374.
  • Masoudi, E., Holling, H. & Wong, W.K. (2017). Application of imperialist competitive algorithm to fond minimax and standardized maximin optimal designs. Computational Statistics & Data Analysis, 113, 330-345.
  • Böhning, D., Rocchetti,I., Alfó, M., & Holling, H. (2016). A flexible ratio regression approach for zero-truncated capture-recapture counts. Biometrics, 72, 697-706.
  • Bürkner P. C., Doebler P., & Holling, H. (2016). Optimal design of the Wilcoxon-Mann-Whitney-test. Biometrical Journal, 59, 25-40.
  • Graßhoff, U., Holling, H., & Schwabe,R. (2016). Optimal Design for the Rasch Poisson-Gamma Model. In Kunert, J., Müller,C., Atkinson, A. (Eds.). Advances in Model-Oriented Design and Analysis, 133-141.
  • Holling, H., & Schwabe, R. (2016). Statistical Optimal Design Theory. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of Item Response Theory, 2, 313-339.
  • Masoudi, E., Holling, H., & Wong, W. K. (2016). Application of imperialist competitive algorithm to find minimax and standardized maximin optimal designs. Computational Statistics & Data Analysis, 113, 330-345.
  • 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.
  • 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. 75-82. Cham: Springer.
  • Doebler, P., & Holling, H. (2015). Meta-analysis of diagnostic accuracy and ROC curves with covariate adjusted semi-parametric mixtures. Psychometrika, 1084-1104.
  • Holling. H., Böhning, W., & Böhning, D. (2015). The covariate-adjusted frequency plot for the Rasch Poisson counts model. Thailand Statistician, 67-78.
  • 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.
  • Charoensawat, S., Böhning, W., Böhning, D., & Holling, H. (2014). Meta-analysis and meta-modelling for diagnostic problems. BMC Medical Research Methodology, 14-56.
  • Sangnawakij, P., Böhning, D., Adams, S., Stanton, M., & Holling, H. (2014). Statistical methodology for estimating the mean difference in a meta-analysis without study-specific variance information. Statistics in Medicine, 36, 1395-1413.
  • 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.
  • 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.) Moda 10-Advances in Model-Oriented Design and Analysis. 117-124, Heidelberg: Physica.
  • Holling, H., Böhning, W., Böhning, D., & Formann, A. K. (2013). The Covariate-Adjusted Frequency Plot. Statistical Methods in Medical Research, 25, 2, 902-916.
  • Holling, H., & Schwabe, R. (2013). An introduction to optimal design. Zeitschrift für Psychologie, 221, 3, 124-144.
  • Doebler, P., Holling, H., & Böhning, D. (2012). A Mixed Model Approach to Meta-Analysis of Diagnostic 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 random coefficients. Journal of Statistical Planning and Inference ,142, 1108-1113.
  • Graßhoff, U., Großmann, H., Holling, H., & Schwabe, R. (2012). Optimal Design for Discrete 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, 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, 76, 495-519.
  • 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.
  • 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.

 

 

Meta-Analysis

  • Reinhold M., Bürkner P. C., Holling H. (2018). Effects of Expressive Writing on Depressive Symptoms – A Meta-Analysis. Clinical Psychologie: Science and Practice.
  • Scharfen, J., Peters, J. M. & Holling, H. (2018). Retest Effects in Cognitive Ability Tests: A Meta-Analysis. Intelligence, 67, 44-66
  • Scharfen, J., Blum, D., & Holling, H. (2018). Response time reduction due to retesting in mental speed tests: a meta-analysis. Journal of Intelligence, 6, 1, 6.
  • Scharfen, J., Jansen, K., & Holling, H. (2018). Retest effects in working memory capacity tests: a meta-analysis. Psychonomic Bulletin & Review.
  • Blum, D. & Holling, H. (2017). Spearman’s Law of Diminishing Returns. A meta-analysis. Intelligence, 65, 60-66.
  • Bürkner, P., Bittner, N., Holling, H., & Buhlmann, U. (2017). D-Cycloserine Augmentation of Behavior Therapy for Anxiety and Obsessive-Compulsive Disorders: A Meta-Analysis. Plos one, 12, 3, doi:10.137.
  • Hodzic, S., Scharfen, J., Ripoll, P., Holling, H., & Zenasni, F. (2017). How efficient are emotional intelligence trainings: a meta-analysis. Emotion Review, 1-11, https://doi.org./10.1177/1754073917708613.
  • Johnen, A., Landmeyer, N.C., Bürkner, P.-C., Wiendl, H., Meuth, S.G., & Holling, H. (2017). Distinct cognitive impairments in different disease courses of multiple sclerosis – A systematic review and meta-analysis. Neuroscience & Bio-behavioral Reviews, 80, 568-578.
  • Chodura, S., Kuhn, J.-T., & Holling, H. (2015). Interventions for children with mathematical difficulties: A meta-analysis. Zeitschrift für Psychologie, 223, 2, 129-144.
  • 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 Development Disabilities, 165, 152-167.
  • Skodzik, T., Holling, H., & Pedersen, A. (2013). Long-term memory performance in adult ADHD - a Meta-Analysis. Journal of Attention Disorders. Online publication, 21, 4, 267-283.

Assessment, Cognitive Abilities

  • Forthmann, B., Jendryczko, D., Scharfen, J., Kleinkorres, R., Benedek, M. & Holling, H. (2019). Creative ideation, broad retrieval ability, and processing speed: A confirmatory study of nested cognitive abilities. Intelligence, 75, 59-72. doi:10.1016/j.intell.2019.04.006
  • Forthmann, B., Bürkner, P. C., Szardenings, C., Benedek, M. & Holling, H. (2019). A new perspective on the multidimensionality of divergent thinking tasks. Frontiers in Psychology: Cognition, 10, 985. doi:10.3389/fpsyg.2019.00985
  • Blum, D. & Holling, H. (2018). Automatic generation of figural analogies with the IMak package. Frontiers in Psychology, 9(1286), 1-13.
  • Forthmann, B., Oyebade, O., Ojo, A., Günther, F. & Holling. H. (2018). Application of latent semantic analysis to diver-gent thinking is biased by elaboration. Journal of Creative Behavior. doi:10.1002/jocb.240.
  • Forthmann, B., Lips, C., Szardenings, C., Scharfen, J., & Holling, H. (2018). Are speedy brains needed when divergent thinking is speeded - or unspeeded? Journal of Creative Behavior. doi:10.1002/jocb.350
  • Forthmann, B., Çelik, P., Holling, H., Storme, M., & Lubart, T. (2018). Item response modeling of divergent-thinking tasks: A comparison of Rasch’s Poisson model with a two-dimensional model extension. International Journal of Creativity and Problem Solving, 28(2), 83-95.
  • Forthmann, B., Szardenings, C. & Holling, H. (2018). Understanding the confounding effect of fluency in divergent thinking scores: Revisiting average scores to quantify artifactual correlation. Psychology of Aesthetics, Creativity, and the Arts.
  • Forthmann, B., Regeher, S., Seidel, J., Holling, H., Celik., P., Storme, M. & Lubart, T. (2018). Revisting the interactive effect of multicultural experiences and openness to experience on divergent thinking. International Journal of Intercultural Relations. doi:0.1016/j.ijentrel.2017.10.002.
  • Szardeinings, C. A., Kuhn, J.-T., Ranger, J. & Holling, H. (2018). A Diffusion Model Analysis of Magnitude Comparison in Children with and without Dyscalculia: Care of Response and Ability Are Related to Both Mathematical Achievement and Stimuli. Frontiers in Psychology. doi:org/10.3389/fpsyg.2017.01615.
  • Forthmann, B., Holling, H., Çelik, P., Storme, M., & Lubart, T. (2017). Typing speed as a confounding variable and the measurement of quality in divergent thinking. Creativity Research Journal, 29, 257-269.
  • Ngamjarus, C., Chongsuvivatwong, V., McNeil, E. & Holling, H. (2017). Enhancement of learning on sample size calculation with a smartphone application: a cluster-randomized controlled trial. The Southeast Asian Journal of Tropical Medicine and Public Health, 48, 240-252.
  • Raddatz, J., Kuhn, J.-T., Holling, H., Doebel, C. (2017). Comorbidity of Arithmetic and Reading Disorder: Basic Number Processing and Calculation in Children with Learning Impairments. Journal of Learning Disabilities, 50, 298-308.
  • Schwenk, C., Kuhn, J.-T., Gühne, D., Doebler, P. & Holling, H. (2017). Auf Goldmünzenjagd: Psychometrische Kennwerte verschiedener Scoringansätze bei computergestützter Lernverlaufsdiagnostik im Bereich Mathematik. Empirische Sonderpädagogik, 9, 123–142
  • Storme, M., Çelik, P., Camargo, A., Forthmann, B., Holling, H., & Lubart, T. (2017). The effect of forced language switching during divergent thinking: A study on bilinguals' originality of ideas. Frontiers in Psychology: Cognition, 8, 1-7. doi:10.3389/fpsyg.2017.02086.
  • Blum, D., Holling, H., Galibert, M.S., & Forthmann, B. (2016). Task difficulty prediction of figural analogies. Intelligence, 56, 72-81.
  • 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.
  • Forthmann, B., Wilken, A., Doebler, P., & Holling, H. (2016) Strategy induction enhances creativity in figural divergent thinking. Journal of Creative Behavior, doi:10.1002/jocb.159.
  • Forthmann, B., Holling, H., Zandi, N., Gerwig, A., Celik, P., Storme, M., & Lubart, T. (2016). Missing creativity: The effect of cognitive workload on rater (dis-)agreement in subjective divergent-thinking scores. Thinking Skills and Creativity, 23, 129-139.
  • 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 impairments. Journal of Learning Disabilities, 50, 298-308.
  • Stein, A., Wunderlich, R., Lau, P., Engell, A., Wollbrink, A., Shaykevich, A., Kuhn, J.-T., Holling, H., Rudack, C., & Pantev, C. (2016). Clinical trial on tonal tinnitus with tailor-made notched music training. BMC Neurology, 16, 1-17.
  • Alavash, M., Doebler, P., Holling, H., Thiel, C. M., & Gießing, C. (2015). Is functional integration of resting state brain networks an unspecific biomarker for working memory performance? NeuroImage, 108, 182-193.
  • Doebler, P., & Holling, H. (2015). A processing speed test based on rule-based item generation: An analysis with the Rasch Poisson Counts model. Learning and Individual Differences, 2015, 1-8.
  • 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.
  • Kuhn, J.-T., Raddatz, J., Holling, H., & Dobel, C. (2013). Dyskalkulie vs. Rechenschwäche: Basisnumerische Verarbeitung in der Grundschule. Lernen und Lernstörungen, 2, 229-247.
  • Skodzik, T., Holling, H., & Pedersen, A. (2013). Long-term memory performance in adult ADHD - a Meta-Analysis. Journal of Attention Disorders. Online publication, 21, 4, 267-283.
  • 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 dif-ferent 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.
  • 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.