A Bayesian Approach Towards Missing Covariate Data in Multilevel Latent Regression Models
Faculty/Professorship: | Survey Statistics and Data Analysis ; Statistics and Econometrics |
Author(s): | Aßmann, Christian ![]() ![]() |
Title of the Journal: | Psychometrika : a journal of quantitative psychology |
ISSN: | 1860-0980 |
Publisher Information: | New York : Springer |
Year of publication: | 2022 |
Pages: | 34 |
Language(s): | English |
Remark: | This paper uses data from the German National Educational Panel Study (NEPS), see Blossfeld and Roßbach (2019) and https://doi.org/10.5157/NEPS:SC4:10.0.0 |
DOI: | 10.1007/s11336-022-09888-0 |
Peer Reviewed: | Ja |
International Distribution: | Ja |
Type: | Article |
URI: | https://fis.uni-bamberg.de/handle/uniba/56766 |
Release Date: | 28. November 2022 |
Project: | Ein Bayesianischer Modellrahmen für die Auswertung von Daten aus Iängsschnittlichen Large-scale Assessments |

originated at the
University of Bamberg
University of Bamberg