16 Publikationen
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2023 | Preprint | Veröffentlicht | PUB-ID: 2983249Kiefer, C.; Woud, M. L.; Blackwell, S. E.; Mayer, A. (2023): Average Treatment Effects on Binary Outcomes with Stochastic Covariates PsyArXivPUB | DOI | Download (ext.) | Preprint
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2023 | Preprint | Veröffentlicht | PUB-ID: 2983248Kiefer, C.; Wilker, S.; Mayer, A. (2023): Interactions Between Latent Variables in Count Regression Models PsyArXivPUB | DOI | Download (ext.) | Preprint
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2023 | Preprint | Veröffentlicht | PUB-ID: 2983399Kiefer, C.; Lugauer, B.; Mayer, A. (2023): Definition and Identification of Causal Ratio EffectsPUB | DOI | Download (ext.)
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2023 | Report | PUB-ID: 2978117Claus, A. M.; Lampel, G.; Kiefer, C.; Mayer, A.; Wiese, B. S. (2023): Interdisciplinary, Multidisciplinary, and Monodisciplinary Study Programs in Germany: A classification scheme. LIfBi Leibniz Institute for Educational Trajectories.PUB | DOI | Download (ext.)
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2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2969141Kiefer, C.; Claus, A. M.; Jung, A. J.; Wiese, B. S.; Mayer, A. (2023): Discovering Exceptional Development of Commitment in Interdisciplinary Study Programs Zeitschrift für Psychologie,231:(1): 53-64.PUB | PDF | DOI | Download (ext.) | WoS
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2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2966192Kiefer, C.; Lemmerich, F.; Langenberg, B.; Mayer, A. (2022): Subgroup discovery in structural equation models Psychological MethodsPUB | DOI | WoS | PubMed | Europe PMC
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2021 | Preprint | Veröffentlicht | PUB-ID: 2957850Kiefer, C.; Lemmerich, F.; Langenberg, B.; Mayer, A. (2021): Subgroup Discovery in Structural Equation Models PsyArXivPUB | DOI | Download (ext.)
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2021 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2966364Mayer, A.; Kiefer, C.; Langenberg, B.; Lemmerich, F. (2021): Using subgroup discovery and latent growth curve modeling to identify unusual developmental trajectories. In: Uwe Engel; Anabel Quan-Haase; Sunny Xun Liu; Lars Lyberg (Hrsg.): Handbook of Computational Social Science, Volume 2. Data Science, Statistical Modelling, and Machine Learning Methods. London: Routledge. S. 244-268.PUB | DOI
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2020 | Dissertation | Veröffentlicht | PUB-ID: 2946666Kiefer, C. (2020): Average and conditional treatment effects on count outcomes : a moment-based approach. Aachen: RWTH Aachen.PUB | DOI | Download (ext.)
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2020 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2946667Lemmerich, F.; Kiefer, C.; Langenberg, B.; Cacho Aboukhalil, J.; Mayer, A. (2020): Mining Exceptional Mediation Models. In: Denis Helic; Gerhard Leitner; Martin Stettinger; Alexander Felfernig; Zbigniew W. Raś (Hrsg.): Foundations of Intelligent Systems. 25th International Symposium, ISMIS 2020, Graz, Austria, September 23–25, 2020, Proceedings. Cham: Springer . (Lecture Notes in Computer Science, 12117). S. 318-328.PUB | DOI
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2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2950353Kiefer, C.; Rosseel, Y.; Wiese, B. S.; Mayer, A. (2018): Modeling and predicting non-linear changes in educational trajectories: The multilevel latent growth components approach Psychological Test and Assessment Modeling,60:(2): 189–22.PUB | PDF
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