In Review

  • König, L., Zitzmann, S., & Hecht, M. (in review). Strategizing AI utilization for psychological literature screening: A comparative analysis of machine learning algorithms and key factors to consider. https://doi.org/10.31234/osf.io/nc8hs
  • Nedderhoff, A., Zitzmann, S., & Hecht, M. (in review). Advancing forecasting in psychology: A tutorial and illustration of a novel approach based on LSTM neural networks for analyzing longitudinal data. PsyArXiv. https://osf.io/ukqtc/.

Accepted / In Press

  • Bardach, L., Röhl, S., Oczlon, S., Schumacher, A., Lüftenegger, M., Lavelle-Hill, R., . . . Zitzmann, S. (in press). Cultural diversity climate at school: A meta-analysis of relationships with intergroup, academic, and socioemotional outcomes. Psychological Bulletin.
  • Walther, J.-K., Hecht, M., & Zitzmann, S. (in press). Shrinking small sample problems in multilevel structural equation modeling via regularization of the sample covariance matrix. Structural Equation Modeling.
  • Zitzmann, S., Lindner, C., & Hecht, M. (in press). A straightforward and valid correction to Nathoo et al.’s Bayesian within-subject credible interval. Journal of Mathematical Psychology.
  • Zitzmann, S., Wagner, W., Lavelle-Hill, R., Jung, A., Jach, H., Loreth, L., . . . Hecht, M. (in press). On the role of variation in measures, the worth of underpowered studies, and the need for tolerance among researchers: Some more reflections on Leising et al. from a methodological, statistical, and socialpsychological perspective. Personality Science, 5, 1-13.

2024

  • Bardach, L., Lohmann, J., Horstmann, K., Zitzmann, S., & Hecht, M. (2024). From intellectual investment trait theory to dynamic intellectual investment trait and state theory: Theory extension, methodological advancement, and empirical illustration. Journal of Research in Personality, 108. https://doi.org/10.1016/j.jrp.2023.104445 
  • Campos, D. G., Fütterer, T., Gfrörer, T., Lavelle-Hill, R., Murayama, K., König, L., Hecht, M., Zitzmann, S., & Scherer, R. (2024). Screening smarter, not harder: A comparative analysis of machine learning screening algorithms and heuristic stopping criteria for systematic reviews in educational research. Educational Psychology Review, 36, Article 19. https://doi.org/10.1007/s10648-024-09862-5 
  • Flunger, B., Verdonschot, A., Zitzmann, S., Hornstra, L., & van Gog, T. (2024). A Bayesian approach to students’ perceptions of teachers’ autonomy support. Learning and Instruction, Advance online publication. https://doi.org/10.1016/j.learninstruc.2023.101873
  • Godara, M., Hecht, M., & Singer, T. (2024). Training-related improvements in mental well-being through reduction in negative interpretation bias: A randomized trial of online socio-emotional dyadic and mindfulness interventions. Journal of Affective Disorders. Advance Online Publication. https://doi.org/10.1016/j.jad.2024.03.037 
  • Hecht, M., Walther, J.-K., Arnold, M., & Zitzmann, S. (2024). Finding the optimal number of persons (N) and time points (T) for maximal power in dynamic longitudinal models. Structural Equation Modeling , 31 , 535–551. https://doi.org/10.1080/10705511.2023.2230520 
  • König, L., Zitzmann, S., Fütterer, T., Campos, D. G., Scherer, R., & Hecht, M (2024). An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research. Research Synthesis Methods, 15,(6). https://doi.org/10.1002/jrsm.1762
  • Lohmann, J. F., Zitzmann, S., & Hecht, M. (2023). Studying between-subject differences in trends and dynamics: Introducing the random coefficients continuous-time latent curve model with structured residuals. Structural Equation Modeling: A Multidisciplinary Journal, 31, 151-164. https://doi.org/10.1080/10705511.2023.2192889
  • Matthaeus, H., Godara, M., Silveira, S., Hecht, M., Voelkle, M., & Singer, T. (2024). Reducing loneliness through the power of practicing together: A randomized controlled trial of online dyadic socio-emotional vs. mindfulness-based training. International Journal of Environmental Research and Public Health, 21, Article 570. https://doi.org/10.3390/ijerph21050570 
  • Orona, G. A., Pritchard, D., Arum, R., Eccles, J., Dang, Q.-V., Copp, D., . . . Zitzmann, S. (2023). Epistemic virtue in higher education: Testing the mechanisms of intellectual character development. Current Psychology, 43, 3102-8116. https://psycnet.apa.org/doi/10.1007/s12144-023-05005-1
  • Preusler, S., Fleckenstein, J., Zitzmann, S., Baumert, J., & Möller, J. (2024). Two-way immersion promotes additional language learning: Performance of bilingual sixth-grade students in English as a third language. International Journal of Bilingual Education and Bilingualism, 27, 910-922. https://doi.org/10.1080/13670050.2024.2307436
  • Wagner, W., Zitzmann, S., & Hecht, M. (2024). HBMIRT: A SAS macro for estimating uni- and multidimensional 1- and 2-parameter item response models in small (and large!) samples. Behavior Research Methods, 56, 4130-4161. https://doi.org/10.3758/s13428-024-02366-8 
  • Walther, J. K., Hecht, M., Nagengast, B., & Zitzmann, S. (2024). To be long or to be wide: How data format influences convergence and estimation accuracy in multilevel structural equation modelling. Structural Equation Modeling: A Multidisciplinary Journal, 31(5),759-774. https://doi.org/10.1080/10705511.2024.2320050 
  • Zitzmann, S., Bardach, L., Horstmann, K. T., Ziegler, M., & Hecht, M. (2024). Quantifying individual personality change more accurately by regression-based change scores. Structural Equation Modeling: A Multidisciplinary Journal. Advance online publication. https://doi.org/10.1080/10705511.2023.2274800
  • Zitzmann, S., & Lindner, C. (2024). How to assess response. European Archives of Psychiatry and Clinical Neuroscience, Advance online publication. https://doi.org/10.1007/s00406-024-01834-8 
  • Zitzmann, S., Lindner, C., Leucht, C., & Leucht, S. (2024). Taking uncertainty in the assessment of response into account: An advanced guideline for computing responder rates in clinical trials. European Neuropsychopharmacology, 85, 3–4. https://doi.org/10.1016/j.euroneuro.2024.03.008
  • Zitzmann, S., Orona, G. A., Lohmann, J. F., König, C., Bardach, L., & Hecht, M. (2024). Novick meets bayes: Improving the assessment of individual students in educational practice and research by capitalizing on assessors’ prior beliefs. Educational and Psychological Measurement, 0(0). https://doi.org/10.1177/00131644241296139

2023

  • Freuli, F., Held, L., & Heyard, R. (2023). Replication success under questionable research practices - A simulation study. Statistical Science, 38, 621-639. https://doi.org/10.1214/23-sts904 
  • Crewther, B. T., Hecht, M., Grillot, R. L., Eisenbruch, A. B., Catena, T., Potts, N., Kilduff, L. P., Cook, C. J., Maestripieri, D., & Roney, J. R. (2023). Day-to-day coordination of the stress and reproductive axes: A continuous-time analysis of within-person testosterone and cortisol relationships in athletic and healthy men. Physiology & Behavior, 263, Article 114104. https://doi.org/10.1016/j.physbeh.2023.114104
  • Fütterer, T., Steinhauser, R., Zitzmann, S., Scheiter, K., Lachner, A., & Stürmer, K. (2023). Development and validation of a test to assess teachers’ knowledge about how to operate technology. Computers and Education Open, 5, 1-10. http://dx.doi.org/10.1016/j.caeo.2023.100152
  • Hecht*, M., Horstmann*, K. T., Arnold, M., Sherman, R. A., & Voelkle, M. C. (2023). Modeling dynamic personality theories in a continuous-time framework: An illustration. Journal of Personality, 91, 718–735. https://doi.org/10.1111/jopy.12769 
  • Helm, F., Wolff, F., Möller, J., Zitzmann, S., Marsh, H. W., & Dicke, T. (2023). Individualized teacher frame of reference and student self-concept within and between school subjects. Journal of Educational Psychology, 115, 309–239. https://awspntest.apa.org/doi/10.1037/edu0000737
  • Hübner, N., Wagner, W., Zitzmann, S., & Nagengast, B. (2023). How strong is the evidence for a causal reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement. Educational Psychology Review, 35, 1-45. https://psycnet.apa.org/doi/10.1007/s10648-023-09724-6
  • Lindner, C., Zitzmann, S., Klusmann, U., & Zimmermann, F. (2023). From procrastination to frustration – How delaying tasks can affect study satisfaction and dropout intentions over the course of university studies. Learning and Individual Differences, 108, 1-12. https://doi.org/10.1016/j.lindif.2023.102373
  • Silveira, S., Hecht, M., Voelkle, M. C., & Singer, T. (2023). Tend-and-befriend and rally around the flag effects during the COVID-19 pandemic: Differential longitudinal change patterns in multiple aspects of social cohesion. European Journal of Social Psychology. Advance online publication. https://doi.org/10.1002/ejsp.2974 
  • Orona, G. A., Eccles, J. S., Zitzmann, S., Fischer, C., & Arum, R. (2023). Cognitive development in undergraduate emerging adults: How course-taking breadth supports skill formation. Contemporary Educational Psychology, 74, 1-17. https://doi.org/10.1016/j.cedpsych.2023.102206
  • Reininger, K. M., Biel, H. M., Hennig, T., Zitzmann, S., Weigel, A., Spitzer, C., . . .Löwe, B. (2023). Beliefs about emotions predict psychological stress related to somatic symptoms. British Journal of Clinical Psychology, 62, 699-716. https://doi.org/10.1111/bjc.12438
  • Wagner, W., Hecht, M., & Zitzmann, S. (2023). A SAS macro for automated stopping of Markov chain Monte Carlo estimation in Bayesian modeling with PROC MCMC. Psych, 5, 966–982. https://doi.org/10.3390/psych5030063 
  • Zitzmann, S. (2023). A cautionary note regarding multilevel factor score estimates from lavaan. Psych, 5, 38–49. https://doi.org/10.3390/psych5010004
  • Zitzmann, S., Lindner, C., Leucht, C., & Leucht, S. (2023). A potential issue with PANSS responder analysis. Schizophrenia Research, 261, 287–290. https://doi.org/10.1016/j.schres.2023.10.009
  • Zitzmann, S., Machts, N., Hübner, N., Schauber, S., Möller, J., & Lindner, C. (2023). The yet underestimated importance of communicating findings from educational trials to teachers, schools, school authorities, or policy makers [comment on Brady et al. (2023)]. Educational Psychology Review, 35, 1-5. http://dx.doi.org/10.1007/s10648-023-09776-8
  • Zitzmann, S., Weirich, S., & Hecht, M. (2023). Accurate standard errors in multilevel modeling with heteroscedasticity: A computationally more efficient jackknife technique. Psych, 5, 757–769. https://doi.org/10.3390/psych5030049 

2022

  • Jindra, C., Sachse, K. A., & Hecht, M. (2022). Dynamics between reading and math proficiency over time in secondary education – observational evidence from continuous time models. Large-Scale Assessments in Education, 10, Article 22. https://doi.org/10.1186/s40536-022-00136-6 
  • Lohmann, J. F., Zitzmann, S., Voelkle, M. C., & Hecht, M. (2022). A primer on continuous-time modeling in educational research: An exemplary application of a continuous-time latent curve model with structured residuals (CT-LCM-SR) to PISA Data. Large-Scale Assessments in Education, 10, Article 5. https://doi.org/10.1186/s40536-022-00126-8 
  • Parrisius, C., Gaspard, H., Zitzmann, S., Trautwein, U., & Nagengast, B. (2022). The "situative nature" of competence and value beliefs and the predictive power of autonomy support: A multilevel investigation of repeated observations. Journal of Educational Psychology, 114, 791–814. https://psycnet.apa.org/doi/10.1037/edu0000680
  • Preusler, S., Zitzmann, S., Baumert, J., & Möller, J. (2022). Development of German reading comprehension in two-way immersive primary schools. Learning and Instruction, 79, 1–10. https://doi.org/10.1016/j.learninstruc.2022.101598
  • Silveira, S., Hecht, M., Adli, M., Voelkle, M. C., & Singer, T. (2022). Exploring the structure and interrelations of time-stable psychological resilience, psychological vulnerability, and social cohesion. Frontiers in Psychiatry, 13, Article 804763. https://doi.org/10.3389/fpsyt.2022.804763  
  • Silveira, S., Hecht, M., Matthaeus, H., Adli, M., Voelkle, M. C., & Singer, T. (2022). Coping with the COVID-19 pandemic: Perceived changes in psychological vulnerability, resilience and social cohesion before, during and after lockdown. International Journal of Environmental Research and Public Health, 19, Article 3290. https://doi.org/10.3390/ijerph19063290 
  • Weirich*, S., Hecht*, M., Becker, B., & Zitzmann, S. (2022). Comparing group means with the total mean in random samples, surveys, and large-scale assessments: A tutorial and software illustration. Behavior Research Methods, 54, 1051–1062. https://doi.org/10.3758/s13428-021-01553-1
  • Zitzmann, S., Lohmann, Julian F., Krammer, G., Helm, C., Aydin, B., & Hecht, M. (2022). A Bayesian EAP-based nonlinear extension of Croon and van Veldhoven’s model for analyzing data from micro–macro multilevel designs. Mathematics, 10, Article 842. https://doi.org/10.3390/math10050842 
  • Zitzmann, S., Loreth, L., Reininger, K. M., & Simon, B. (2022). Does respect foster tolerance? (Re)analyzing and synthesizing data from a large research project using meta-analytic techniques. Personality and Social Psychology Bulletin, 48, 823–843. https://doi.org/10.1177/01461672211024422
  • Zitzmann, S., Wagner, W., Hecht, M., Helm, C., Fischer, C., Bardach, L., & Göllner, R. (2022). How many classes and students should ideally be sampled when assessing the role of classroom climate via student ratings on a limited budget? An optimal design perspective. Educational Psychology Review, 35, 511–536. https://doi.org/10.1007/s10648-021-09635-4 
  • Zitzmann, S., Walther, J.-K., Hecht, M., & Nagengast, B. (2022). What is the Maximum Likelihood estimate when the initial solution to the optimization problem is inadmissible? The case of negatively estimated variances. Psych, 4, 343–356. https://doi.org/10.3390/psych4030029 

2021

  • Crewther, B. T., Hecht, M., & Cook, C. J. (2021). Diurnal within-person coupling between testosterone and cortisol in healthy men: evidence of positive and bidirectional time-lagged associations using a continuous-time model. Adaptive Human Behavior and Physiology, 7, 89–104. https://doi.org/10.1007/s40750-021-00162-8
  • Godara, M., Silveira, S., Matthäus, H., Heim, C., Voelkle, M., Hecht, M., Binder,E. B., & Singer, T. (2021). Investigating differential effects of socio-emotional and mindfulness-based online interventions on mental health, resilience and social capacities during the COVID-19 pandemic: The study protocol. PLOS ONE, 16, Article e0256323. https://doi.org/10.1371/journal.pone.0256323 
  • Hecht, M., Voelkle, M. C. (2021). Continuous-time modeling in prevention research: An illustration. International Journal of Behavioral Development, 45, 19–27. https://doi.org/10.1177/0165025419885026 
  • Hecht, M., Weirich, S., & Zitzmann, S. (2021). Comparing the MCMC efficiency of JAGS and Stan for the multi-level intercept-only model in the covariance- and mean-based and classic parametrization. Psych, 3, 751–779. https://doi.org/10.3390/psych3040048 
  • Hecht, M., & Zitzmann, S. (2021). Exploring the unfolding of dynamic effects with continuous-time models: Recommendations concerning statistical power to detect peak cross-lagged effects.Structural Equation Modeling: A Multidisciplinary Journal, 28, 894–902. https://doi.org/10.1080/10705511.2021.1914627 
  • Hecht, M., & Zitzmann, S. (2021). Sample size recommendations for continuous-time models: Compensating shorter time-series with higher numbers of persons and vice versa. Structural Equation Modeling: A Multidisciplinary Journal, 28, 229–236. https://doi.org/10.1080/10705511.2020.1779069 
  • Schaefer, C. D., Zitzmann, S., Loreth, L., Paffrath, J., Grabow, H., Loewy, M., & Simon, B. (2021). The meaning of respect under varying context conditions. Journal of Social and Political Psychology, 9, 536–552. https://doi.org/10.5964/jspp.7313
  • Schmerse, D., & Zitzmann, S. (2021). Early school adjustment: Do social integration and persistence mediate the effects of school-entry skills on later achievement? Learning and Instruction, 71, 1–12. https://doi.org/10.1016/j.learninstruc.2020.101374
  • Wolff, F., Zitzmann, S., & Möller, J. (2021). Moderators of dimensional comparison effects: A comprehensive replication study putting prior findings on five moderators to the test and going beyond. Journal of Educational Psychology, 113, 621–640. https://doi.org/10.1037/edu0000505
  • Zitzmann, S., & Helm, C. (2021). Multilevel analysis of mediation, moderation, and nonlinear effects in small samples, using expected a posteriori estimates of factor scores. Structural Equation Modeling, 28, 529-546. https://doi.org/10.1080/10705511.2020.1855076
  • Zitzmann, S., Helm, C., & Hecht, M. (2021). Prior specification for more stable Bayesian estimation of multilevel latent variable models in small samples: A comparative investigation of two different approaches. Frontiers in Psychology, 11, Article 611267. https://doi.org/10.3389/fpsyg.2020.611267 
  • Zitzmann, S., & Loreth, L. (2021). Regarding an "almost anything goes" attitude toward methods in psychology. Frontiers in Psychology, 12, 1–4. https://doi.org/10.3389/fpsyg.2021.612570
  • Zitzmann, S., Lüdtke, O., Robitzsch, A., & Hecht, M. (2021). On the performance of Bayesian approaches in small samples: A Comment on Smid, McNeish, Miocevic, and van de Schoot (2020). Structural Equation Modeling: A Multidisciplinary Journal, 28, 40–50. https://doi.org/10.1080/10705511.2020.1752216
  • Zitzmann, S., Weirich, S., & Hecht, M. (2021). Using the effective sample size as the stopping criterion in Markov chain Monte Carlo with the Bayes module in Mplus. Psych, 3, 336–347. https://doi.org/10.3390/psych3030025 

2020

  • Crewther, B. T., Hecht, M., Potts, N., Kilduff, L. P., Drawer, S., Marshall, E., & Cook, C. J. (2020). A longitudinal investigation of bidirectional and time-dependent interrelationships between testosterone and training motivation in an elite rugby environment. Hormones and Behavior, 126, Article 104866. https://doi.org/10.1016/j.yhbeh.2020.104866
  • Hardt, K., Hecht, M., & Voelkle, M. C. (2020). Robustness of individual score methods against model misspecification in autoregressive panel models. Structural Equation Modeling: A Multidisciplinary Journal, 27, 240–254. https://doi.org/10.1080/10705511.2019.164275 
  • Hecht, M., Gische, C., Vogel, D., & Zitzmann, S. (2020). Integrating out nuisance parameters for computationally more efficient Bayesian estimation – An illustration and tutorial. Structural Equation Modeling: A Multidisciplinary Journal, 27, 483–493. https://doi.org/10.1080/10705511.2019.1647432 
  • Hecht, M., & Zitzmann, S. (2020). A computationally more efficient Bayesian approach for estimating continuous-time models. Structural Equation Modeling: A Multidisciplinary Journal, 27, 829–840. https://doi.org/10.1080/10705511.2020.1719107 
  • Machts, N., Zitzmann, S., & Möller, J. (2020). Dimensionality of teacher judgments on a competency-based report card in elementary school. Learning and Instruction, 67, 1–10. https://doi.org/10.1016/j.learninstruc.2020.101328
  • Möller, J., Zitzmann, S., Helm, F., Machts, N., & Wolff, F. (2020). A meta-analysis of relations between achievement and self-concept. Review of Educational Research, 90, 376–419.https://doi.org/10.3102/0034654320919354
  • Reininger, K. M., Schaefer, C. D., Zitzmann, S., & Simon, B. (2020). Dynamics of respect: Evidence from two different national and political contexts. Journal of Social and Political Psychology, 8, 542–559. https://doi.org/10.5964/jspp.v8i2.1199
  • Schauber, S. K., & Hecht, M. (2020). How sure can we be that a student really failed? On the measurement precision of individual pass-fail decisions from the perspective of Item Response Theory. Medical Teacher, 42, 1374–1384. https://doi.org/10.1080/0142159X.2020.1811844
  • Schüttpelz-Braun, K., Hecht, M., Hardt, K., Karay, Y., Zupanic, M., & Kämmer, J. (2020). Institutional strategies related to test-taking behavior in low stakes assessment. Advances in Health Sciences Education, 25, 321–335. https://doi.org/10.1007/s10459-019-09928-y 
  • Teerling, A., Zitzmann, S., Igler, J., Schlitter, T., Ohle-Peters, A., McElvany, N., & Köller, O. (2020). Kommunikative Rahmenbedingungen beim Change Management in der Schule [Communicative conditions in change management within schools]. Zeitschrift für Arbeits- und Organisationspsychologie, 64, 249–262. https://doi.org/10.1026/0932-4089/a000326

2019

  • Hardt, K., Hecht, M., Oud, J. H. L., & Voelkle, M. C. (2019). Where have the persons gone? An illustration of individual score methods in autoregressive panel models. Structural Equation Modeling: A Multidisciplinary Journal, 26, 310–323. https://doi.org/10.1080/10705511.2018.1517355 
  • Hecht, M., Hardt, K., Driver, C. C., & Voelkle, M. C. (2019). Bayesian continuous-time Rasch models. Psychological Methods, 24, 516–537. https://doi.org/10.1037/met0000205
  • Preusler, S., Zitzmann, S., Paulick, I., Baumert, J., & Möller, J. (2019). Ready to read in two languages? Testing the native language hypothesis and the majority language hypothesis in two-way immersion students. Learning and Instruction, 64, 1–8. https://doi.org/10.1016/j.learninstruc.2019.101247
  • Simon, B., Eschert, S., Schaefer, C. D., Reininger, K. M., Zitzmann, S., & Smith, H. J. (2019). Disapproved, but tolerated: The role of respect in outgroup tolerance. Personality and Social Psychology Bulletin, 45, 406–415. https://doi.org/10.1177/0146167218787810
  • Simon, B., Reininger, K. M., Schaefer, C. D., Zitzmann, S., & Krys, S. (2019). Politicization as an antecedent of polarization: Evidence from two different political and national contexts. British Journal of Social Psychology, 58, 769–785. https://doi.org/10.1111/bjso.12307
  • Zitzmann, S., & Hecht, M. (2019). Going beyond convergence in Bayesian estimation: Why precision matters too and how to assess it. Structural Equation Modeling: A Multidisciplinary Journal, 26, 646–661. https://doi.org/10.1080/10705511.2018.1545232

2018

  • Schauber, S. K., & Hecht, M., & Nouns, Z. M. (2018). Why assessment in medical education needs a solid foundation in modern test theory. Advances in Health Sciences Education, 23, 217–232. https://doi.org/10.1007/s10459-017-9771-4
  • Zitzmann, S. (2018). A computationally more efficient and more accurate stepwise approach for correcting for sampling error and measurement error. Multivariate Behavioral Research, 53, 612–632. https://doi.org/10.1080/00273171.2018.1469086

2017

  • Hecht, M., Siegle, T., & Weirich, S. (2017). A model for the estimation of testlet response time to optimize test assembly in paper-and-pencil large-scale assessments. Journal for Educational Research Online, 9, 32–51. https://www.waxmann.com/index.php?eID=download&id_artikel=ART102889&uid=frei 
  • Heitmann, P., Hecht, M., Scherer, R., & Schwanewedel, J. (2017). "Learning science is about facts and language learning is about being discursive": An empirical investigation of students' disciplinary beliefs in the context of argumentation. Frontiers in Psychology, 8, Article 946. https://doi.org/10.3389/fpsyg.2017.00946 
  • Weirich, S., Hecht, M., Penk, C., Roppelt, A., & Böhme, K. (2017). Item position effects are moderated by changes in test-taking effort. Applied Psychological Measurement, 50, 115–129. https://doi.org/10.1177/0146621616676791
  • Wellnitz, N., Hecht, M., Heitmann, P., Kauertz, A., Mayer, J., Sumfleth, E., & Walpuski, M. (2017). Modellierung des Kompetenzteilbereichs naturwissenschaftliche Untersuchungen. Zeitschrift für Erziehungswissenschaft, 20, 556–584. https://doi.org/10.1007/s11618-016-0721-3

2016

  • Gittel, B., Deutschländer, R., & Hecht, M. (2016). Conveying moods and knowledge-what-it-is-like through lyric poetry: An empirical study of authors’ intentions and readers’ responses. Scientific Study of Literature, 6, 131–163. https://doi.org/10.1075/ssol.6.1.07git
  • Zitzmann, S., Lüdtke, O., Robitzsch, A., & Marsh, H. W. (2016). A Bayesian approach for estimating multilevel latent contextual models. Structural Equation Modeling, 23, 661–679. https://doi.org/10.1080/10705511.2016.1207179

2015

  • Hecht, M., Weirich, S., Siegle, T., & Frey, A. (2015). Effects of design properties on parameter estimation in large-scale assessments. Educational and Psychological Measurement, 75, 1021–1044. https://doi.org/10.1177/0013164415573311
  • Hecht, M., Weirich, S., Siegle, T., & Frey, A. (2015). Modeling booklet effects for nonequivalent group designs in large-scale assessment. Educational and Psychological Measurement, 75, 568–584. https://doi.org/10.1177/0013164414554219
  • Schauber, S. K., Hecht, M., Nouns, Z. M., Kuhlmey, A., & Dettmer, S. (2015). The role of environmental and individual characteristics in the development of student achievement: A comparison between a traditional and a problem-based-learning curriculum. Advances in Health Sciences Education, 20, 1033– 1052. https://doi.org/10.1007/s10459-015-9584-2
  • Zitzmann, S., Lüdtke, O., & Robitzsch, A. (2015). A Bayesian approach to more stable estimates of group-level effects in contextual studies. Multivariate Behavioral Research, 50, 688–705. https://doi.org/10.1080/00273171.2015.1090899

2014

  • Heitmann, P., Hecht, M., Schwanewedel, J., & Schipolowski, S. (2014). Students' argumentative writing skills in science and first-language education: Commonalities and differences. International Journal of Science Education, 36, 3148–3170. https://doi.org/10.1080/09500693.2014.962644
  • Weirich, S., Haag, N., Hecht, M., Böhme, K., Siegle, T., & Lüdtke, O. (2014). Nested multiple imputation in large-scale assessments. Large-scale Assessments in Education, 2, Article 9. https://doi.org/10.1186/s40536-014-0009-0 
  • Weirich, S., Hecht, M., & Böhme, K. (2014). Modeling item position effects using generalized linear mixed models. Applied Psychological Measurement, 38, 535–548. https://doi.org/10.1177/0146621614534955

2013

  • Knops, A., Zitzmann, S., & McCrink, K. (2013). Examining the presence and determinants of operational momentum in childhood. Frontiers in Psychology, 4, 1–14. https://doi.org/10.3389/fpsyg.2013.00325
  • Schauber, S. K., Hecht, M., Nouns, Z. M., & Dettmer, S. (2013). On the role of biomedical knowledge in the acquisition of clinical knowledge. Medical Education, 47, 1223–1235. https://doi.org/10.1111/medu.12229 

*Shared first authorship.
  Open Access