Elwood Hartman
Biographic Data
| ID | 763871 |
|---|---|
| NAME | Elwood Hartman |
| GIVEN NAMES | Elwood |
| FAMILY NAME | Hartman |
| SIGNATURE | HARTMAN E |
| AFFILIATIONS | University of California, Berkeley |
| ORCID | 0000-0003-4824-5405 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 132 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1979 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Assessing Nonignorable Response: Sensitivity Analysis for Survey Weighting, with Applications to Survey Estimates of Covid-19 Vaccination Uptake
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…
Improving precision through design and analysis in experiments with noncompliance
Even in the best-designed experiment, noncompliance can complicate analysis. While the intent-to-treat effect remains identified, randomization alone no longer identifies the complier average causal effect (CACE). Instrumental variables approaches, which rely on the exclusion restriction, can suffer from high variance, particularly when the experiment has a low compliance rate. We provide a framework which broadens the set of design and analysis …
Sensitivity Analysis for Survey Weights
Survey weighting allows researchers to account for bias in survey samples, due to unit nonresponse or convenience sampling, using measured demographic covariates. Unfortunately, in practice, it is impossible to know whether the estimated survey weights are sufficient to alleviate concerns about bias due to unobserved confounders or incorrect functional forms used in weighting. In the following paper, we propose two sensitivity analyses for the ex…
Multilevel Calibration Weighting for Survey Data
In the November 2016 U.S. presidential election, many state-level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading explanation for this polling miss is that the precipitous decline in traditional polling response rates led to greater reliance on statistical methods to adjust for the corresponding bias—and that these methods failed to adjust for important interactions between key var…
Generalizing toward Nonrespondents: Effect Estimates in Survey Experiments Are Broadly Similar for Eager and Reluctant Participants
Survey experiments on probability samples are a popular method for investigating population-level causal questions due to their strong internal validity. However, lower survey response rates and an increased reliance on online convenience samples raise questions about the generalizability of survey experiments. We examine this concern using data from a collection of 50 survey experiments which represent a wide range of social science studies. Rec…
Elements of External Validity: Framework, Design, and Analysis
The external validity of causal findings is a focus of long-standing debates in the social sciences. Although the issue has been extensively studied at the conceptual level, in practice few empirical studies include an explicit analysis that is directed toward externally valid inferences. In this article, we make three contributions to improve empirical approaches for external validity. First, we propose a formal framework that encompasses four d…
Equivalence Testing for Regression Discontinuity Designs
Regression discontinuity (RD) designs are increasingly common in political science. They have many advantages, including a known and observable treatment assignment mechanism. The literature has emphasized the need for “falsification tests” and ways to assess the validity of the design. When implementing RD designs, researchers typically rely on two falsification tests, based on empirically testable implications of the identifying assumptions, to…
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: The Affective Roots of Issue Proximity Between Voters and Parties
From Our Readers
A Profile of French National Character
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…
Elements of External Validity: Framework, Design, and Analysis
The external validity of causal findings is a focus of long-standing debates in the social sciences. Although the issue has been extensively studied at the conceptual level, in practice few empirical studies include an explicit analysis that is directed toward externally valid inferences. In this article, we make three contributions to improve empirical approaches for external validity. First, we propose a formal framework that encompasses four d…
Dead Man Walking: The Affective Roots of Issue Proximity Between Voters and Parties
Sensitivity Analysis for Survey Weights
Survey weighting allows researchers to account for bias in survey samples, due to unit nonresponse or convenience sampling, using measured demographic covariates. Unfortunately, in practice, it is impossible to know whether the estimated survey weights are sufficient to alleviate concerns about bias due to unobserved confounders or incorrect functional forms used in weighting. In the following paper, we propose two sensitivity analyses for the ex…
Multilevel Calibration Weighting for Survey Data
In the November 2016 U.S. presidential election, many state-level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading explanation for this polling miss is that the precipitous decline in traditional polling response rates led to greater reliance on statistical methods to adjust for the corresponding bias—and that these methods failed to adjust for important interactions between key var…
Equivalence Testing for Regression Discontinuity Designs
Regression discontinuity (RD) designs are increasingly common in political science. They have many advantages, including a known and observable treatment assignment mechanism. The literature has emphasized the need for “falsification tests” and ways to assess the validity of the design. When implementing RD designs, researchers typically rely on two falsification tests, based on empirically testable implications of the identifying assumptions, to…
Generalizing toward Nonrespondents: Effect Estimates in Survey Experiments Are Broadly Similar for Eager and Reluctant Participants
Survey experiments on probability samples are a popular method for investigating population-level causal questions due to their strong internal validity. However, lower survey response rates and an increased reliance on online convenience samples raise questions about the generalizability of survey experiments. We examine this concern using data from a collection of 50 survey experiments which represent a wide range of social science studies. Rec…
Improving precision through design and analysis in experiments with noncompliance
Even in the best-designed experiment, noncompliance can complicate analysis. While the intent-to-treat effect remains identified, randomization alone no longer identifies the complier average causal effect (CACE). Instrumental variables approaches, which rely on the exclusion restriction, can suffer from high variance, particularly when the experiment has a low compliance rate. We provide a framework which broadens the set of design and analysis …
A Profile of French National Character
From Our Readers
Dead Man Walking: The Affective Roots of Issue Proximity Between Voters and Parties
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…
Equivalence Testing for Regression Discontinuity Designs
Regression discontinuity (RD) designs are increasingly common in political science. They have many advantages, including a known and observable treatment assignment mechanism. The literature has emphasized the need for “falsification tests” and ways to assess the validity of the design. When implementing RD designs, researchers typically rely on two falsification tests, based on empirically testable implications of the identifying assumptions, to…
Elements of External Validity: Framework, Design, and Analysis
The external validity of causal findings is a focus of long-standing debates in the social sciences. Although the issue has been extensively studied at the conceptual level, in practice few empirical studies include an explicit analysis that is directed toward externally valid inferences. In this article, we make three contributions to improve empirical approaches for external validity. First, we propose a formal framework that encompasses four d…
Improving precision through design and analysis in experiments with noncompliance
Even in the best-designed experiment, noncompliance can complicate analysis. While the intent-to-treat effect remains identified, randomization alone no longer identifies the complier average causal effect (CACE). Instrumental variables approaches, which rely on the exclusion restriction, can suffer from high variance, particularly when the experiment has a low compliance rate. We provide a framework which broadens the set of design and analysis …
Sensitivity Analysis for Survey Weights
Survey weighting allows researchers to account for bias in survey samples, due to unit nonresponse or convenience sampling, using measured demographic covariates. Unfortunately, in practice, it is impossible to know whether the estimated survey weights are sufficient to alleviate concerns about bias due to unobserved confounders or incorrect functional forms used in weighting. In the following paper, we propose two sensitivity analyses for the ex…
Multilevel Calibration Weighting for Survey Data
In the November 2016 U.S. presidential election, many state-level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading explanation for this polling miss is that the precipitous decline in traditional polling response rates led to greater reliance on statistical methods to adjust for the corresponding bias—and that these methods failed to adjust for important interactions between key var…
Generalizing toward Nonrespondents: Effect Estimates in Survey Experiments Are Broadly Similar for Eager and Reluctant Participants
Survey experiments on probability samples are a popular method for investigating population-level causal questions due to their strong internal validity. However, lower survey response rates and an increased reliance on online convenience samples raise questions about the generalizability of survey experiments. We examine this concern using data from a collection of 50 survey experiments which represent a wide range of social science studies. Rec…
Assessing Nonignorable Response: Sensitivity Analysis for Survey Weighting, with Applications to Survey Estimates of Covid-19 Vaccination Uptake
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…
Mathematics (9 works) · Computer Science (8 works) · Econometrics (8 works) · Statistics (8 works) · Advanced Causal Inference Techniques (6 works) · Statistical Methods and Bayesian Inference (5 works) · Electoral Systems and Political Participation (4 works) · Psychology (4 works) · Survey Methodology and Nonresponse (4 works) · Weighting (4 works)