Karoline A Sachse
Biographic Data
| ID | 8867907 |
|---|---|
| NAME | Karoline A Sachse |
| GIVEN NAMES | Karoline A |
| FAMILY NAME | Sachse |
| SIGNATURE | SACHSE K A |
| AFFILIATIONS | Institute for Educational Quality Improvement, Humboldt-Universität zu Berlin |
| ORCID | 0000-0001-6688-1267 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Targeted Maximum Likelihood Estimation for Causal Inference With Observational Data—The Example of Private Tutoring
State-of-the-art causal inference methods for observational data promise to relax assumptions threatening valid causal inference. Targeted maximum likelihood estimation (TMLE), for example, is a template for constructing doubly robust, semiparametric, efficient substitution estimators, providing consistent estimates if the outcome or treatment model is correctly specified. Compared to standard approaches, it reduces the risk of misspecification b…
Covid-19-related school closures and mathematical performance—findings from a study with grade 3 students in Germany
Introduction Due to the COVID-19 pandemic, measures were taken that had a considerable impact on the situation in schools. In Germany, these measures lasted more than a year and ranged from school closures and distance learning to alternating teaching phases with small groups. In the present study, we examined whether third-grade students’ mathematics performance changed in different content domains before and after the COVID-19-related changes i…
Teaching in Times of Covid-19
To depict the situation during the school closures in spring 2020 that were implemented to contain the spread of COVID-19, we conducted a self-constructed online survey on distance teaching among teachers regarding their teaching practices in this new situation, the challenges they experienced, and the prerequisites for successful distance teaching. The sample consisted of voluntarily participating German elementary ( n = 857) and secondary schoo…
When Nonresponse Mechanisms Change
Mechanisms causing item nonresponses in large-scale assessments are often said to be nonignorable. Parameter estimates can be biased if nonignorable missing data mechanisms are not adequately modeled. In trend analyses, it is plausible for the missing data mechanism and the percentage of missing values to change over time. In this article, we investigated (a) the extent to which the missing data mechanism and the percentage of missing values chan…
No prominent works on this page.
When Nonresponse Mechanisms Change
Mechanisms causing item nonresponses in large-scale assessments are often said to be nonignorable. Parameter estimates can be biased if nonignorable missing data mechanisms are not adequately modeled. In trend analyses, it is plausible for the missing data mechanism and the percentage of missing values to change over time. In this article, we investigated (a) the extent to which the missing data mechanism and the percentage of missing values chan…
Teaching in Times of Covid-19
To depict the situation during the school closures in spring 2020 that were implemented to contain the spread of COVID-19, we conducted a self-constructed online survey on distance teaching among teachers regarding their teaching practices in this new situation, the challenges they experienced, and the prerequisites for successful distance teaching. The sample consisted of voluntarily participating German elementary ( n = 857) and secondary schoo…
Covid-19-related school closures and mathematical performance—findings from a study with grade 3 students in Germany
Introduction Due to the COVID-19 pandemic, measures were taken that had a considerable impact on the situation in schools. In Germany, these measures lasted more than a year and ranged from school closures and distance learning to alternating teaching phases with small groups. In the present study, we examined whether third-grade students’ mathematics performance changed in different content domains before and after the COVID-19-related changes i…
Targeted Maximum Likelihood Estimation for Causal Inference With Observational Data—The Example of Private Tutoring
State-of-the-art causal inference methods for observational data promise to relax assumptions threatening valid causal inference. Targeted maximum likelihood estimation (TMLE), for example, is a template for constructing doubly robust, semiparametric, efficient substitution estimators, providing consistent estimates if the outcome or treatment model is correctly specified. Compared to standard approaches, it reduces the risk of misspecification b…
Geography (3 works) · Advanced Causal Inference Techniques (2 works) · Educational Innovations and Technology (2 works) · German (2 works) · Mathematics (2 works) · Mathematics education (2 works) · Medicine (2 works) · Psychology (2 works) · Statistical Methods and Bayesian Inference (2 works) · Statistics (2 works)