Missing-data publications
Work on missing data, multiple imputation and robust imputation models
This list is a subset of the complete list of publications and contains all missing-data related work. See research for what connects these papers. Every entry carries a BibTeX button that copies its record to the clipboard.
2026
Kleinke, K., & Gaisbauer, H. (2026). From Probabilistic to Deterministic Missingness: When Predictive Mean Matching Breaks Down Under MAR [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/db7tz_v1
2024
Kleinke, K., & Reinecke, J. (2024). Multiple imputation of incomplete panel data based on a piecewise growth curve model – an evaluation and application to juvenile delinquency data. In M. Stemmler, W. Wiedermann, & F. Huang (Eds.), Dependent data in social sciences research: Forms, issues and methods of analysis (2nd ed., pp. 589–615). Springer Nature. https://doi.org/10.1007/978-3-031-56318-8_24
Kleinke, K., Fritsch, M., Stemmler, M., & Lösel, F. (2024). Multiple imputation of longitudinal data – a comparison of robust imputation methods regarding sample size requirements, with an application to corporal punishment data. In M. Stemmler, W. Wiedermann, & F. Huang (Eds.), Dependent data in social sciences research: Forms, issues and methods of analysis (2nd ed., pp. 565–588). Springer Nature. https://doi.org/10.1007/978-3-031-56318-8_23
2022
Kleinke, K., & Reinecke, J. (2022). How to and how not to impute incomplete count data. Proceedings from the 9th European Congress of Methodology, Universitat de València, 86–92. https://doi.org/10.7203/PUV-OA-438-5
2021
Kleinke, K. (2021). Estimation of partially observed non-linear terms in a multilevel model: An evaluation of the robustness of ad hoc and state-of-the-art missing data methods. Psychological Test and Assessment Modeling, 63(3), 432–455.
Kleinke, K., Fritsch, M., Stemmler, M., Reinecke, J., & Lösel, F. (2021). Quantile regression-based multiple imputation of missing values – an evaluation and application to corporal punishment data. Methodology, 17(3), 205–230. https://doi.org/10.5964/meth.2317
Kleinke, K., Reinecke, J., & Weins, C. (2021). The development of delinquency during adolescence: A comparison of missing data techniques revisited. Quality & Quantity, 55(3), 877–895. https://doi.org/10.1007/s11135-020-01030-5
Spiess, M., Kleinke, K., & Reinecke, J. (2021). Proper multiple imputation of clustered or panel data. In P. Lynn (Ed.), Advances in longitudinal survey methodology (pp. 424–446). John Wiley & Sons.
2020
Kleinke, K., Reinecke, J., Salfrán, D., & Spiess, M. (2020). Applied multiple imputation. Advantages, pitfalls, new developments and applications in R. Springer Nature.
2019
Kleinke, K., & Reinecke, J. (2019). Countimp version 2 – A multiple imputation package for incomplete count data (Technical report). University of Siegen, Department of Education Studies; Psychology.
2018
Kleinke, K. (2018). Multiple imputation by predictive mean matching when sample size is small. Methodology, 14(1), 3–15. https://doi.org/10.1027/1614-2241/a000141
2017
Kleinke, K. (2017). Multiple imputation under violated distributional assumptions – a systematic evaluation of the assumed robustness of predictive mean matching. Journal of Educational and Behavioral Statistics, 42(4), 371–404. https://doi.org/10.3102/1076998616687084
2015
Kleinke, K., & Reinecke, J. (2015). Multiple imputation of multilevel count data. In U. Engel, B. Jann, P. Lynn, A. Scherpenzeel, & P. Sturgis (Eds.), Improving survey methods: Lessons from recent research (pp. 381–396). Routledge.
Kleinke, K., & Reinecke, J. (2015). Multiple imputation of overdispersed multilevel count data. In U. Engel (Ed.), Survey measurements: Techniques, data quality and sources of error (pp. 209–226). Campus.
2013
Kleinke, K., & Reinecke, J. (2013). Multiple imputation of incomplete zero-inflated count data. Statistica Neerlandica, 67(3), 311–336. https://doi.org/10.1111/stan.12009
Kleinke, K., & Reinecke, J. (2013). countimp 1.0 – A multiple imputation package for incomplete count data (Technical report). University of Bielefeld, Faculty of Sociology. https://doi.org/10.13140/RG.2.1.3889.3286
2011
Kleinke, K., Stemmler, M., Reinecke, J., & Lösel, F. (2011). Efficient ways to impute incomplete panel data. Advances in Statistical Analysis, 95, 351–373. https://doi.org/10.1007/s10182-011-0179-9