Saskia Bartholomäus
Biographic Data
| ID | 9570591 |
|---|---|
| NAME | Saskia Bartholomäus |
| GIVEN NAMES | Saskia |
| FAMILY NAME | Bartholomäus |
| SIGNATURE | BARTHOLOMÄUS S |
| AFFILIATIONS | GESIS - Leibniz Institute for the Social Sciences |
| ORCID | 0000-0002-0083-1539 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Prediction-Based Adaptive Designs for Reducing Wave Nonresponse Rates and Bias in Panel Surveys
Machine learning (ML)-based nonresponse prediction in panel surveys enables selective interventions. However, the optimal use of ML predictions in Adaptive Survey Design (ASD) remains uncertain. We propose a method that integrates field experiment results on incentives, questionnaire length, and questionnaire content with ML-based propensity models to simulate ASD strategies ex-post with minimal assumptions. Using German panel data, we show that …
Survey data collection during the Covid-19 pandemic in Germany
The COVID-19 pandemic created a high demand for rapid data collection while also posing major challenges to collecting timely, high-quality population survey data on public health, and health-related behavior and attitudes. In the Survey Data Collection during the COVID-19 Pandemic (SDCCP) project, we examined how data collection standards evolved during the pandemic and what challenges the national survey infrastructure in Germany was facing. Ou…
The Impact of the Covid-19 Pandemic on the Design of Repeated Cross-Sectional and Panel Surveys in Germany
The COVID-19 pandemic posed a major challenge for the implementation of population surveys, particularly longitudinal studies such as repeated cross-sectional and panel surveys. Since these surveys aim to measure change in many indicators over time, any modifications to their design must be carefully considered as they might compromise comparability over time. In our study, we examined how the pandemic affected the data collection of longitudinal…
No prominent works on this page.
The Impact of the Covid-19 Pandemic on the Design of Repeated Cross-Sectional and Panel Surveys in Germany
The COVID-19 pandemic posed a major challenge for the implementation of population surveys, particularly longitudinal studies such as repeated cross-sectional and panel surveys. Since these surveys aim to measure change in many indicators over time, any modifications to their design must be carefully considered as they might compromise comparability over time. In our study, we examined how the pandemic affected the data collection of longitudinal…
Prediction-Based Adaptive Designs for Reducing Wave Nonresponse Rates and Bias in Panel Surveys
Machine learning (ML)-based nonresponse prediction in panel surveys enables selective interventions. However, the optimal use of ML predictions in Adaptive Survey Design (ASD) remains uncertain. We propose a method that integrates field experiment results on incentives, questionnaire length, and questionnaire content with ML-based propensity models to simulate ASD strategies ex-post with minimal assumptions. Using German panel data, we show that …
Survey data collection during the Covid-19 pandemic in Germany
The COVID-19 pandemic created a high demand for rapid data collection while also posing major challenges to collecting timely, high-quality population survey data on public health, and health-related behavior and attitudes. In the Survey Data Collection during the COVID-19 Pandemic (SDCCP) project, we examined how data collection standards evolved during the pandemic and what challenges the national survey infrastructure in Germany was facing. Ou…
Survey Methodology and Nonresponse (2 works) · Census and Population Estimation (1 works) · COVID-19 Digital Contact Tracing (1 works) · Data collection (1 works) · Data quality (1 works) · Data-Driven Disease Surveillance (1 works) · nonresponse (1 works) · nonresponse bias (1 works) · Pandemic (1 works) · Panel survey (1 works)