Research Interests

My research program spans from psychological measurement and psychometrics over machine learning methods to multilevel modeling. I aim at developing new methods in each area and at their intersection, and I also disseminate the newly developed methods to empirical researchers via software contributions in R.

I also teach statistics courses at the Bachelor, Master, and postgraduate level, such as introductory statistics, psychological assessment, computer-based data analysis, structural equation modeling, multilevel modeling, and machine learning methods. I also enjoy to support empirical researchers building up their statistical and psychometric models as a statistical consultant. My teaching and consulting activities also inspire my methodological work.

Publications

Under review

Dukic, J., Johann, A., Henninger, M., & Ehlert, U. (under review) Salivary sex steroids in the female reproductive transition phase from pregnancy to postpartum: A longitudinal latent class analysis.

Strobl, C., Rothacher, Y., Theiler, S., & Henninger, M. (under review). Detecting interactions with random forests: A comment on Gries’ words of caution and suggestions for improvement.

Rohde, J., Henninger, M., McEneaney, C., Xiyang, Xu A., Wong, J., Mazzaferro, T., Friedman, O., Rahman, N., Kleim, B. & Brown, A. (under review) Digital self-efficacy training and its effects on self-efficacy and mental health outcome: A randomized controlled trial.

Henninger, M. & Strobl, C. (under review). Local interpretation techniques for machine learning methods: Theoretical background, pitfalls and interpretation of LIME and Shapley values. Preprint.

Fokkema, M., Henninger, M., & Strobl., C (under review). One model may not fit all: Subgroup detection using model-based recursive partitioning.

Recher, D., Rohde, J., Da Poian, J., Henninger, M., Brogli, L., Huber, R., Karlen, W., Lustenberger, C., & Kleim, B. (under review). Targeted memory reactivation during sleep improves emotional memory modulation following imagery rescripting.

Rohde, J., Marciniak, M., Henninger, M., Homann, S., Ries, A., Paersch, C., Friedman, O., Brown, A., & Kleim, B. (under review). Efficacy of a digital self-efficacy training in stressed university students: A randomized control trial. Preprint

Peer-reviewed publications

Ulitzsch, E., Henninger, M., & Meiser, T. (in press). Differences in response-scale usage are ubiquitous in cross-country comparisons and a potential driver of elusive relationships. Nature scientific reports. Comment on Sorokowski et al., (2023). OSF

Sengewald, M.-A., Henninger, M., Bechtloff, P, & Kubik, V. (in press). Familiengerechte Chancen für eine wissenschaftliche Karriere in der psychologischen Forschung? Eine Bestandsaufnahme zur Vereinbarkeit beruflicher und familiärer Anforderungen im Fachbereich Psychologie mit zielgerichteten Unterstützungsmaßnahmen. [Family-friendly opportunities for a scientific career in psychological research? An inventory of the compatibility of professional and family requirements in the field of psychology with targeted support measures]. OSF

Zimmer, F., Henninger, M., & Debelak, R. (in press). Sample size planning for complex study designs: A tutorial for the mlpwr package. Behavior Research Methods. Preprint

Paersch, C., Recher, D. Schulz, A., Henninger, M., Schlup, B., Künzler, F., Homan, S., Kowatsch, T., Fisher, A., Horn, A., & Kleim, B. (in press). Self-efficacy predicts avoidance in anxiety disorder patients’ daily life and early treatment response during transdiagnostic cognitive behavior therapy. Clinical Psychological Science.

Brandt, H., Henninger, M., Ulitzsch, E., Kleinke, K., & Schäfer, T. (in press). Responsible research assessment in the area of methodological or quantitative research: A comment on Gärtner et al. (2022). Meta-Psychology. Preprint

Rohde, J., Marciniak, M. A., Henninger, M., Homann, S., Ries, A., Paersch, C., Egger, S., Seifritz, E., Brown, A., & Kleim, B. (in press). Investigating relationships between self-efficacy, mood, and anxiety using digital technologies: A randomized controlled trial. JMIR Formative Research. doi: 10.2196/ 45749.

Henninger, M., Plieninger, H., & Meiser, T. (2023). The effect of response formats on response style strength: An experimental comparison. European Journal of Psychological Assessment. doi: 10.1027/ 1015-5759/a000779. Preprint

Henninger, M., Debelak R., Rothacher, Y., & Strobl, C. (2023). Interpretable machine learning for psychological research: Opportunities and pitfalls. Psychological Methods. doi: 10.1037/met0000560. Preprint

Henninger, M., Debelak, R., & Strobl, C. (2023). A new stopping criterion for Rasch trees based on the Mantel-Haenszel effect size measure for differential item functioning. Educational Psychological Measurement, 83, 181-212. doi:10.1177/ 00131644221077135. Preprint

Henninger, M., Meiser, T. (2023). Quality control: Response style modeling. In: Tierney, R.J., Rizvi, F., Erkican, K. (Eds.), International Encyclopedia of Education, Volume 14. Elsevier. https://dx.doi.org/10.1016/B978-0-12-818630-5.10041-7.

Paz Castro, R., Henninger, M., Schaub, M. P., & Salis Gross, C. (2022). Changes in attitudes towards smoking during smoking cessation courses for Turkish- and Albanian-speaking migrants in Switzerland and its association with smoking behavior: A latent change score approach. Frontiers in Psychology, section Health Psychology. doi: 10.3389/fpsyg.2022.1032091

Henninger, M. (2021). A novel Partial Credit extension using varying thresholds to account for response styles. Journal of Educational Measurement, 58, 104-129 doi:10.1111/jedm.12268. Preprint

Henninger, M. & Plieninger, H. (2021). Different styles, different times: How response times can inform our knowledge about the response process in rating scale measurement. Assessment, 28, 1301-1319. doi:10.1177/ 1073191119900003

Henninger, M. & Meiser, T. (2020). Different approaches to modeling response styles in Divide-by-Total Item Response Theory models (Part I): A model integration. Psychological Methods, 25, 560-576. doi: 10.1037/met0000249. Preprint

Henninger, M. & Meiser, T. (2020). Different approaches to modeling response styles in Divide-by-Total Item Response Theory models (Part II): Applications and novel extensions. Psychological Methods, 25, 577-595. doi: 10.1037/met0000268. Preprint

Meiser, T., Plieninger, H., & Henninger, M. (2019). IRTree models with ordinal and multidimensional decision nodes for response styles and trait-based rating responses. British Journal of Mathematical and Statistical Psychology, 72, 201-216. doi:10.1111/bmsp.12158

Frey, D., Henninger, M., Lübke, R., & Kluge, A. (2016). Einführung und konzeptionelle Klärung. In D. Frey (Ed.), Psychologie der Werte: Von Achtsamkeit bis Zivilcourage - Basiswissen aus Psychologie und Philosophie (pp. 1–12). Berlin, Heidelberg: Springer Berlin Heidelberg. doi: 10.1007/ 978-3-662-48014-4_1

Henninger, M. (2016). Resilienz. in D. Frey (Ed.), Psychologie der Werte: Von Achtsamkeit bis Zivilcourage - Basiswissen aus Psychologie und Philosophie (pp. 157-165). Berlin, Heidelberg: Springer Berlin Heidelberg. doi: 10.1007/ 978-3-662-48014-4_14

Ettlin, F., Bröder, A., & Henninger, M. (2015). A new task format for investigating information search and organization in multi-attribute decisions. Behavior Research Methods, 47, 506-518. doi:10.3758/s13428-014-0482-y

Invited Talks

Detecting heterogeneity between persons using techniques from psychometrics, machine learning, and their intersection (Steffi Pohl, Chair of Methods and Evaluation, FU Berlin; 02 / 2024)

Interpretable machine learning: Shape, relevance, and interactions of predictor effects (Claudia Peus, Chair of Research and Science Management, Technical University Munich; 11 / 2023)

Detecting heterogeneity using methods from psychometrics, machine learning, and multilevel modeling (Eva Ceulemans, Quantitative Psychology and Interindividual Differences, KU Leuven; 05 / 2023)

Interpretable machine learning: Shape, relevance, and interactions of predictor effects (Ginette Lafit, Center for Contextual Psychiatry, KU Leuven; 05 / 2023)

Detecting heterogeneity between persons: Insights using techniques from psychometrics, machine learning methods, and their intersection (Invited speaker at “Advancing quantitative perspectives in education science: A Cambridge-Zurich exchange”, CAMZH; 12 / 2022)

Comparing machine learning based approaches for differential item functioning through illustrative, simulated examples (Christian Aßmann, Timo Gnambs, & Marie-Ann Sengewald, Leibniz Institute for Educational Trajectories, Bamberg; 12 / 2022)

A new stopping criterion for Rasch trees based on the Mantel-Haenszel effect size measure for differential item functioning (Oliver Lüdtke & Esther Ullitzsch, Leibniz Institute for Science and Mathematics Education, Kiel; 06 / 2022)

Using the Mantel-Haenszel odds ratio as a stopping criterion in a recursive partitioning procedure to detect differential item functioning in large-scale assessments (Christian Aßman, Timo Gnambs, & Marie-Ann Sengewald, Leibniz Institute for Educational Trajectories, Bamberg; 01 / 2022)

Guest Lecture in “Statistical methods evaluation via advanced simulation techniques” (Benjamin Becker & Martin Hecht, Berlin University Alliance; 05 / 2021)

Interpretable machine learning methods: Opportunities and pitfalls (Eunike Wetzel, University of Koblenz-Landau; 11 / 2020)

Response Styles as threshold shifts in Divide-by-Total IRT model extensions (Markus Bühner, Ludwig-Maximilian-University Munich; 03 / 2019)

Response Styles IRT models as tools to investigate heterogeneous response scale use (Carolin Strobl, University of Zurich; 01 / 2019)

Teaching and Student Supervision

Teaching

I am teaching diagnostic assessment, research methods, and statistics in the Bachelor and Master Psychology program.

Statistics 1.1 (Lecture; Level: B.Sc.; Fall 2022, Fall 2023, University of Zurich)

Statistics 1.1 (Supervision of Tutors; Level: B.Sc.; Fall 2020, University of Zurich)

Multilevel modeling in psychological research (Level: M.Sc.; Spring 2020, Spring 2021 & Spring 2022 University of Zurich)

Latent variable models and multilevel modeling (Level: M.Sc.; Spring 2018 & Spring 2019, University of Mannheim)

Data analysis using SPSS and R (Level: B.Sc.; Fall 2016 – Fall 2019, University of Mannheim)

Psychological testing and assessment (Level: B.Sc.; Spring 2016 & Spring 2017, University of Mannheim)

Invited and Pre-Conference Workshops & Summer Schools

Machine learning and interpretable machine learning with R (Invited workshop at the Research Data Center (FDZ) of the Insitute for Educational Quality Development (IQB) in Berlin, Germany; February 2024). More information here

Machine learning and interpretable machine learning with R (Invited pre-conference workshop at the European Congress of Methodology, Ghent, Belgium; July 2023). More information here

Modeling heterogeneity of response processes in item response theory (SMiP IOPS Summer School at the University of Mannheim, Germany; June 2023). More Information here

Machine learning and interpretable machine learning with R (Full-day pre-conference workshop at the International Meeting of the Psychometric Society, Bologna, Italy; July 2022). More information here

Multilevel modeling using R (Zurich R Courses; April 2022)

Linear Mixed Models with crossed-random effects in experimental research (Juliane Degner, Chair for Social Psychology, University of Hamburg, Germany; Fall 2018)

Student Supervision

Topics: Response biases, estimation precision in multilevel and structural equation modeling, timescales in longitudinal measurement, machine learning methods, interpretability (Level: M.Sc.; University of Mannheim, University of Zurich)

Topics: Response biases, implicit measurement, publication bias, sequential testing, interpretable machine learning, daily diary methods (Level: B.Sc.; University of Mannheim, University of Zurich)

Topics: Item Response Theory, measurement theory, reliability, statistical testing (Research internships; University of Mannheim, University of Zurich)

CV

Academic Positions

since 02/2024 Assistant Professor for Statistics and Data Science at the University of Basel

09/2023 – 01/2024 Senior Research Associate at the University of Zurich

2020 – 2023 Postdoctoral Researcher at the University of Zurich

2016 – 2019 Researcher and Teaching Fellow at the University of Mannheim

Education

2019 Doctorate in Psychology at the University of Mannheim

2015 Master of Science, Psychology at Ludwig-Maximilians University Munich

2013 Bachelor of Science, Psychology at the University of Mannheim

Equality

I am engaged to foster equality, diversity and inclusion in the psychological research community.

Together with Marie-Ann Sengewald, Pia Bechtloff, and Veit Kubik, I assessed how researchers in psychology are affected from and deal with challenges that arise from care work. We aim at making these challenges more visible via panel discussions and discussion within the research community in Germany, Austria, and Switzerland.

For more details on our activities, please visit the homepage of the German Psychological Association.