Evan T R Rosenman
Biographic Data
| ID | 4393440 |
|---|---|
| NAME | Evan T R Rosenman |
| GIVEN NAMES | Evan T R |
| FAMILY NAME | Rosenman |
| SIGNATURE | ROSENMAN E T R |
| AFFILIATIONS | Harvard University |
| ORCID | 0000-0001-5885-2925 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Recalibration of Predicted Probabilities Using the “Logit Shift
The output of predictive models is routinely recalibrated by reconciling low-level predictions with known quantities defined at higher levels of aggregation. For example, models predicting vote probabilities at the individual level in U.S. elections can be adjusted so that their aggregation matches the observed vote totals in each county, thus producing better-calibrated predictions. In this research note, we provide theoretical grounding for one…
Empirical Insights for Improving Sexual Assault Prevention
The empirical science of measuring and preventing sexual assault is in its infancy, especially when considering adolescents in developing nations. We analyze pre-intervention data collected in a two-arm cluster-randomized controlled trial of a classroom-based sexual assault prevention program deployed to Class 6 students around Nairobi, Kenya. We estimate that 7.2% of girls were raped in the prior 12 months. We identify school- and individual-lev…
Recalibration of Predicted Probabilities Using the “Logit Shift
The output of predictive models is routinely recalibrated by reconciling low-level predictions with known quantities defined at higher levels of aggregation. For example, models predicting vote probabilities at the individual level in U.S. elections can be adjusted so that their aggregation matches the observed vote totals in each county, thus producing better-calibrated predictions. In this research note, we provide theoretical grounding for one…
Empirical Insights for Improving Sexual Assault Prevention
The empirical science of measuring and preventing sexual assault is in its infancy, especially when considering adolescents in developing nations. We analyze pre-intervention data collected in a two-arm cluster-randomized controlled trial of a classroom-based sexual assault prevention program deployed to Class 6 students around Nairobi, Kenya. We estimate that 7.2% of girls were raped in the prior 12 months. We identify school- and individual-lev…
Recalibration of Predicted Probabilities Using the “Logit Shift
The output of predictive models is routinely recalibrated by reconciling low-level predictions with known quantities defined at higher levels of aggregation. For example, models predicting vote probabilities at the individual level in U.S. elections can be adjusted so that their aggregation matches the observed vote totals in each county, thus producing better-calibrated predictions. In this research note, we provide theoretical grounding for one…
Computer Science (2 works) · Adolescent Sexual and Reproductive Health (1 works) · Artificial Intelligence (1 works) · Clinical Psychology (1 works) · Clinical Psychology (1 works) · Cluster (spacecraft (1 works) · Cluster randomised controlled trial (1 works) · Criminology (1 works) · Data Analysis with R (1 works) · Econometrics (1 works)