Diagnostik, Differentielle Psychologie, Methodik und Evaluation

Marcel Schmitt

Anschrift

Fortstraße 7
Gebäude H , Raum 107 , 1. OG
76829 Landau

Kontakt

Tel.: +49 6341 280-31199
E-Mail: marcel.schmitt@rptu.de

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Zur Person

  • seit 10/2020: Doktorand im Graduiertenkolleg "Statistical Modeling in Psychology" (SMiP); wissenschaftlicher Mitarbeiter in der Arbeitseinheit "Diagnostik, Differentielle und Persönlichkeitspsychologie, Methodik und Evaluation"
  • 2020: M.Sc. Psychologie, Universität Koblenz-Landau
  • 2017: B.Sc. Psychologie, Universität Koblenz-Landau

Emotionsdifferenzierung und -variabilität

Statistische Modellierung von intensiv-längsschnittlichen Daten

Latente Markov- und Klassenanalyse

Perfektionismus

Zeitschriftenartikel (peer-reviewed)

Schmitt, M. C., Vogelsmeier, L. V. D. E., Erbas, Y., Stuber, S., & Lischetzke, T. (2024). Exploring within-person variability in qualitative negative and positive emotional granularity by means of latent Markov factor analysis. Multivariate Behavioral Research. doi.org/10.1080/00273171.2024.2328381

Schreiner, M. R., Mercier, B., Frick, S., Wiwad, D., Schmitt, M. C., Kelly, J. M., Quevedo Pütter, J. (2022). Measurement issues in the many analysts religion project. Religion, Brain & Behavior, 13(3), 339–341. https://doi.org/10.1080/2153599X.2022.2070260

Hoogeveen, S., Sarafoglou, A., Aczel, B., Aditya, Y., Alayan, A. J., Allen, P. J., Altay, S., Alzahawi, S., Amir, Y., Anthony, F.-S., Appiah, O. K., Atkinson, Q. D., Baimel, A., Balkaya-Ince, M., Balsamo, M., Banker, S., Bartoš, F., Becerra, M., ..., Schmitt, M. C., ..., Wagenmakers, E.-J. (2022). A many-analysts approach to the relation between religiosity and well-being. Religion, Brain & Behavior, 13(3), 237–283. https://doi.org/10.1080/2153599X.2022.2070255

Schmitt, M. C., Prestele, E., & Reis, D. (2021). Perfectionistic cognitions as antecedents of work engagement: Personal resources, personal demands, or both? Collabra: Psychology, 7(1), 25912. https://doi.org/10.1525/collabra.25912

 

Konferenzvorträge

Schmitt, M. C., Vogelsmeier, L. V. D. E., Erbas, Y., Stuber, S., & Lischetzke, T. (2023, June). Latent Markov factor analysis as a statistical tool to explore within-person variability in qualitative emotional granularity. Talk given at the 9th Conference of the Society for Ambulatory Assessment (SAA), Amsterdam, The Netherlands.

Schmitt, M. C., Stuber, S., & Lischetzke, T. (2021, September). Modeling within-person variability of emotion differentiation by means of Latent Markov Factor Analysis (LMFA). Talk given at the 16th Conference of the Section 'Personality Psychology and Psychological Diagnostics' (DPPD) in the German Psychological Society (DGPs), Ulm, Germany (online).

Schmitt, M. C., Prestele, E. & Reis, D. (2021, September). Perfectionistic cognitions and daily work engagement: A daily diary study among employees. Talk given at the 16th Conference of the Section 'Personality Psychology and Psychological Diagnostics' (DPPD) in the German Psychological Society (DGPs), Ulm, Germany (online).

Schmitt, M. C., Prestele, E. & Reis, D. (2021, July). Perfectionistic cognitions as antecedents of work engagement: A daily diary study among employees. Talk given at the 7th Conference of the Society for Ambulatory Assessment (SAA), Zurich, Switzerland (online).

Schmitt, M. (2021, July). Modeling emotion differentiation by means of Latent Markov Factor Analysis (LMFA). Talk given at the 2nd SMiP IOPS Conference, Mannheim, Germany (online).

Schmitt, M., Reis, D. & Prestele, E. (2018, September). Perfectionistic Strivings und Perfectionistic Concerns in Selbst- und Fremdbericht: Eine multimethodale Betrachtung der Zusammenhänge mit Stress und Burnout bei Studierenden. Talk at the 51st Conference of the German Society of Psychology (DGPs), Frankfurt am Main.

 

Posterpräsentationen

Schmitt, M. (2022, June). Examining qualitative differences in emotion differentiation by applying latent Markov factor analysis. Poster presented at the 3rd SMiP IOPS Conference, Leuven, Belgium.

Schmitt, M. C. (2022, March). Modeling emotion differentiation by means of latent Markov factor analysis. Poster presented at the 2022 Annual Conference of the Society for Affective Science (online).

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