Merk, S., Rosman, T., Muis, K., Kelava, A., & Bohl, T. (in press). Topic specific epistemic beliefs: Extending the theory of integrated domains in personal epistemology. Learning and Instruction. Hennings, A., Heil, J., Wagner, A., Rath, M., Moosbrugger, H., Kelava, A., Golotta, M., Hug, S., Riedel, F., Rauch, G., & Feisst, M. (2018). Development and psychometric validation of a shorter
Grissmann, S., Spüler, M., Faller, J., Krumpe, T., Zander, T., Kelava, A., Scharinger, C., & Gerjets, P. (in press). Context sensitivity of EEG-based workload classification under different affective valence. IEEE Transactions on Affective Computing.
Koch, T., Kelava, A., & Eid, M. (in press). Analyzing Different Types of Moderated Method Effects in Confirmatory Factor Models for Structurally Different Methods. Structural Equation Modeling. Graser, J., Heimlich, C., Kelava, A., Hofmann, S.G., Stangier, U., & Schreiber, F. (accepted). Erfassung der Emotionsregulation bei Jugendlichen anhand des „Affective Style Questionnaire (ASQ-Y)“. Diagnostica. Lösch, T., Lüdtke, O., Robitzsch, A., Kelava,
Mayer, A., Umbach, N., Flunger, B., & Kelava, A. (in press). Detailed effect analysis using non-linear structural equation mixture modeling. Structural Equation Modeling.
Less distributional assumptions…. 😉 Kelava, A., Kohler, M., Krzyzak, A., & Schaffland, T. (in press). Nonparametric estimation of a latent variable model. Journal of Multivariate Analysis. http://dx.doi.org/10.1016/j.jmva.2016.10.006
Umbach, N., Naumann, K., Brandt, H., Kelava, A. (in press). Fitting Nonlinear Structural Equation Models in R with Package nlsem. Journal of Statistical Software.
Kelava, A. (in press). A Review of Confirmatory Factor Analysis for Applied Research (Second Edition). Journal of Educational and Behavioral Statistics. Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (Second Edition). New York, NY: The Guilford Press. ISBN: 978-1-4625-1536-3
Brandt, H., Umbach, N., & Kelava, A. (2015). The Standardization of Linear and Nonlinear Effects in Direct and Indirect Applications of Structural Equation Mixture Models for Normal and Nonnormal Data. Front. Psychol. 6:1813. doi: 10.3389/fpsyg.2015.01813 Link
Schnabel, D., Kelava, A., van de Vijver, F. J. R., & Seifert, L. (2015). Examining Psychometric Properties, Measurement Invariance, and Construct Validity of a Short Version of the Test to Measure Intercultural Competence (TMIC-S) in Germany and Brazil. International Journal of Intercultural Relations, 49, 137-155. [doi:10.1016/j.ijintrel.2015.08.002] Link
… gave a talk on “The Statistical Crisis in Science” at the 2015 meeting of the methods section of the German Psychological Society (https://www.metheval.uni-jena.de/fgme2015/). Courageous person. andrewgelman.com