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Erin Hartman

Datos Biográficos

ID4372243
NOMBREErin Hartman
NOMBRESErin
APELLIDOHartman
FIRMAHARTMAN E
AFILIACIONESLondon School of Hygiene & Tropical Medicine
ORCID0000-0001-9499-6109
VERIFICADOSí
TOTAL DE OBRAS5
TOTAL DE CITAS80
OBRAS COMO AUTOR5
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2016
AÑO MÁS RECIENTE DE PUBLICACIÓN2026
ÍNDICE H2
  • Assessing Nonignorable Response

    Open Access•Melody Huang, Elwood Hartman et al.•ARTICLE•Public Opinion Quarterly•2026

    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

    Open Access•Michelle Lokot, Iram Hashmi et al.•ARTICLE•Refuge Canada s Journal on Refuge•2024•Referencias: 15

    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

    Open Access•Devin Caughey, Adam J Berinskey et al.•BOOK•Target Estimation and Adjustment…•2020

    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

    Open Access•Elwood Hartman, Erin Hartman et al.•ARTICLE•American Journal of Political…•2018•Citada por: 61•Referencias: 29

    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

    Open Access•Elias Dinas, Elwood Hartman et al.•ARTICLE•Political Behavior•2016•Citada por: 19•Referencias: 69

  • An Equivalence Approach to Balance and Placebo Tests

    Open Access•Elwood Hartman, Erin Hartman et al.•ARTICLE•American Journal of Political…•2018•Citada por: 61•Referencias: 29

    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

    Open Access•Elias Dinas, Elwood Hartman et al.•ARTICLE•Political Behavior•2016•Citada por: 19•Referencias: 69

  • Dead Man Walking

    Open Access•Elias Dinas, Elwood Hartman et al.•ARTICLE•Political Behavior•2016•Citada por: 19•Referencias: 69

  • An Equivalence Approach to Balance and Placebo Tests

    Open Access•Elwood Hartman, Erin Hartman et al.•ARTICLE•American Journal of Political…•2018•Citada por: 61•Referencias: 29

    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

    Open Access•Devin Caughey, Adam J Berinskey et al.•BOOK•Target Estimation and Adjustment…•2020

    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

    Open Access•Michelle Lokot, Iram Hashmi et al.•ARTICLE•Refuge Canada s Journal on Refuge•2024•Referencias: 15

    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

    Open Access•Melody Huang, Elwood Hartman et al.•ARTICLE•Public Opinion Quarterly•2026

    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 obras) · Econometrics (2 obras) · Electoral Systems and Political Participation (2 obras) · Law (2 obras) · Law (2 obras) · Mathematics (2 obras) · Political science (2 obras) · Psychology (2 obras) · Sampling (signal processing) (2 obras) · Statistical Methods and Bayesian Inference (2 obras)

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