Char  Hilgers

Char Hilgers

Research Topics and Working Areas
  • Missing data
  • Statistics
  • Data science
  • Multiple imputation

Char Hilgers is a PhD student in Sociology at the Humboldt University's Berlin Graduate School of Social Science, funded by the Socio-Economic Panel at DIW Berlin. Their research focuses on statistical techniques for nonresponse in survey settings, in particular when missingness means something. They are interested in refusal, misdirection, and obfuscation in survey settings, and ethical dilemmas around these. They hold a Master's in Industrial and Applied Mathematics and a Bachelor's in Pure Mathematics, and they have worked as a data scientist in forest monitoring, epidemiology, and supply chain forecasting.

Downloads

Lectures

Vortrag

Filling in the Blanks: Augmenting Survey Data Imputation with External Data and Rubin’s Sampling/Importance Resampling Algorithm

Char Hilgers, Sabine Zinn
Den Haag, Niederlande, 05.10.2025 - 09.10.2025
| 65th ISI World Statistics Congress
Moderation

Missing Data, Selection Bias and Informative Censoring in Cross-Sectional and Longitudinal Survey

Angelina Hammon, Char Hilgers, Sabine Zinn
Utrecht, Niederlande, 14.07.2025 - 18.07.2025
| 11th Conference of the European Survey Research Association (ESRA 2025)
Vortrag

Filling in the Blanks: Augmenting Survey Data Imputation with External Data and Rubin’s Sampling/Importance Resampling Algorithm

Char Hilgers, Sabine Zinn
Utrecht, Niederlande, 14.07.2025 - 18.07.2025
| 11th Conference of the European Survey Research Association (ESRA 2025)
Vortrag

Filling in the Blanks: Augmenting Survey Data Imputation with External Data and Rubin’s SIR Algorithm

Char Hilgers
Warschau, Polen, 09.09.2024 - 14.09.2024
| 1st German-Polish Ph.D. Summer School in Economics: University of Warsaw and DIW Berlin
keyboard_arrow_up
Sorry. no id, no template, no output.