Erin Hartman
Biographic Data
| ID | 4372243 |
|---|---|
| NAME | Erin Hartman |
| GIVEN NAMES | Erin |
| FAMILY NAME | Hartman |
| SIGNATURE | HARTMAN E |
| AFFILIATIONS | London School of Hygiene & Tropical Medicine |
| ORCID | 0000-0001-9499-6109 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 80 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Assessing Nonignorable Response
Standard statistical uncertainty measures, like standard errors, are unable to quantify the uncertainty from an unrepresentative sampling process. Existing work has highlighted the potential risk in large datasets, in which larger surveys resulting in more precise estimates can misleadingly overstate the degree of confidence in biased survey results. In this research note, we introduce a sensitivity framework for researchers to transparently summ…
Always the Ideal? Exploring the Risks of Refugee Participation in Research
Researchers in humanitarian settings increasingly encourage refugees and internally displaced persons (IDPs) to participate within broader research processes, beyond solely providing data. However, efforts to increase participation in research may be tokenistic, complicated by the challenges present in humanitarian settings. The assumption that more participation is always good has meant sometimes limited reflection occurs on the challenges assoc…
Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias
We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully…
An Equivalence Approach to Balance and Placebo Tests
Recent emphasis on credible causal designs has led to the expectation that scholars justify their research designs by testing the plausibility of their causal identification assumptions, often through balance and placebo tests. Yet current practice is to use statistical tests with an inappropriate null hypothesis of no difference, which can result in equating nonsignificant differences with significant homogeneity. Instead, we argue that research…
Dead Man Walking
An Equivalence Approach to Balance and Placebo Tests
Recent emphasis on credible causal designs has led to the expectation that scholars justify their research designs by testing the plausibility of their causal identification assumptions, often through balance and placebo tests. Yet current practice is to use statistical tests with an inappropriate null hypothesis of no difference, which can result in equating nonsignificant differences with significant homogeneity. Instead, we argue that research…
Dead Man Walking
Dead Man Walking
An Equivalence Approach to Balance and Placebo Tests
Recent emphasis on credible causal designs has led to the expectation that scholars justify their research designs by testing the plausibility of their causal identification assumptions, often through balance and placebo tests. Yet current practice is to use statistical tests with an inappropriate null hypothesis of no difference, which can result in equating nonsignificant differences with significant homogeneity. Instead, we argue that research…
Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias
We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully…
Always the Ideal? Exploring the Risks of Refugee Participation in Research
Researchers in humanitarian settings increasingly encourage refugees and internally displaced persons (IDPs) to participate within broader research processes, beyond solely providing data. However, efforts to increase participation in research may be tokenistic, complicated by the challenges present in humanitarian settings. The assumption that more participation is always good has meant sometimes limited reflection occurs on the challenges assoc…
Assessing Nonignorable Response
Standard statistical uncertainty measures, like standard errors, are unable to quantify the uncertainty from an unrepresentative sampling process. Existing work has highlighted the potential risk in large datasets, in which larger surveys resulting in more precise estimates can misleadingly overstate the degree of confidence in biased survey results. In this research note, we introduce a sensitivity framework for researchers to transparently summ…
Computer Science (2 works) · Econometrics (2 works) · Electoral Systems and Political Participation (2 works) · Law (2 works) · Law (2 works) · Mathematics (2 works) · Political science (2 works) · Psychology (2 works) · Sampling (signal processing) (2 works) · Statistical Methods and Bayesian Inference (2 works)