Laura Boeschoten
Cited by
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Estimating classification errors under edit restrictions in composite survey-register data using multiple imputation latent class modelling (MILC)
L Boeschoten, D Oberski, T De Waal
Journal of Official Statistics 33 (4), 921-962, 2017
Digital trace data collection through data donation
L Boeschoten, J Ausloos, J Moeller, T Araujo, DL Oberski
arXiv preprint arXiv:2011.09851, 2020
Combining Multiple Imputation and Hidden Markov Modeling to Obtain Consistent Estimates of Employment Status
L Boeschoten, D Filipponi, R Varriale
Journal of Survey Statistics and Methodology, 2020
Estimating the number of serious road injuries per vehicle type in the Netherlands by using multiple imputation of latent classes
L Boeschoten, T de Waal, JK Vermunt
Journal of the Royal Statistical Society: Series A (Statistics in Society …, 2019
Updating latent class imputations with external auxiliary variables
L Boeschoten, DL Oberski, T De Waal, JK Vermunt
Structural Equation Modeling: A Multidisciplinary Journal 25 (5), 750-761, 2018
Instagram use and the well-being of adolescents: Using deep learning to link social scientific self-reports with Instagram data download packages
L Boeschoten, II van Driel, DL Oberski, LJ Pouwels
Companion Publication of the 2020 International Conference on Multimodal …, 2020
How to Obtain Valid Inference under Unit Nonresponse?
L Boeschoten, G Vink, JJCM Hox
Journal of Official Statistics 33 (4), 963-978, 2017
Fair inference on error-prone outcomes
L Boeschoten, EJ van Kesteren, A Bagheri, DL Oberski
arXiv preprint arXiv:2003.07621, 2020
Promises and Pitfalls of Instagram Data Donations
I Van Driel, A Giachanou, JL Pouwels, L Boeschoten, I Beyens, ...
Automatic de-identification of data download packages
L Boeschoten, R Voorvaart, R Van Den Goorbergh, C Kaandorp, ...
Data Science, 1-20, 2021
Privacy-preserving local analysis of digital trace data: A proof-of-concept
L Boeschoten, A Mendrik, E van der Veen, J Vloothuis, H Hu, R Voorvaart, ...
Patterns 3 (3), 100444, 2022
A note on applying the bch method under linear equality and inequality constraints
L Boeschoten, MA Croon, DL Oberski
Journal of Classification 36 (3), 566-575, 2019
Consistent Estimates for Categorical Data Based on a Mix of Adminstrative Data Sources and Surveys
L Boeschoten
Tilburg University, 2019
A note on efficient audit sample selection
L Boeschoten, S Scholtus, A Van Delden
arXiv preprint arXiv:2105.10737, 2021
A framework for digital trace data collection through data donation.
L Boeschoten, J Ausloos, JE Möller, TB Araujo, DL Oberski
CoRR, 2020
Estimating population census tables and their accuracy using Multiple Imputation of Latent Classes (MILC) with multi-source data
L Boeschoten, S Scholtus, T de Waal, J Daalmans, J Vermunt
ITACOSM 2019-Survey and Data Science, 2019
Latent Class Multiple Imputation for multiply observed variables in a combined dataset
L Boeschoten, D Oberski, AG de Waal
Q 2016: European Conference on Quality in Official Statistics, 1-10, 2016
Instagram Use and the Well-Being of Adolescents
L Boeschoten, II van Driel, DL Oberski, L Pouwels
Gelijke schattingen voor categorische data bij een combinatie van registerdata en surveys
L Boeschoten
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