Using the Census Bureau’s surname list to improve estimates of race/ethnicity and associated disparities

Elliott, Marc N.; Morrison, Peter A.; Fremont, Allen; McCaffrey, Daniel F.; Pantoja, Philip; Lurie, Nicole

doi:10.1007/s10742-009-0047-1

Cited by 201 publications

(213 citation statements)

References 12 publications

Supporting

Mentioning

204

Contrasting

Order By: Relevance

“…We begin by describing the Bayesian method developed by Elliott et al (2009). Let the surname and geolocation of voter i be denoted by S i and G i , respectively.…”

Section: The Bayesian Predictionmentioning

confidence: 99%

Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records

2016

View full text Add to dashboard Cite

Edited by Justin GrimmerIn both political behavior research and voting rights litigation, turnout and vote choice for different racial groups are often inferred using aggregate election results and racial composition. Over the past several decades, many statistical methods have been proposed to address this ecological inference problem. We propose an alternative method to reduce aggregation bias by predicting individual-level ethnicity from voter registration records. Building on the existing methodological literature, we use Bayes's rule to combine the Census Bureau's Surname List with various information from geocoded voter registration records. We evaluate the performance of the proposed methodology using approximately nine million voter registration records from Florida, where self-reported ethnicity is available. We find that it is possible to reduce the false positive rate among Black and Latino voters to 6% and 3%, respectively, while maintaining the true positive rate above 80%. Moreover, we use our predictions to estimate turnout by race and find that our estimates yields substantially less amounts of bias and root mean squared error than standard ecological inference estimates. We provide open-source software to implement the proposed methodology.

show abstract

“…We begin by describing the Bayesian method developed by Elliott et al (2009). Let the surname and geolocation of voter i be denoted by S i and G i , respectively.…”

Section: The Bayesian Predictionmentioning

confidence: 99%

Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records

2016

View full text Add to dashboard Cite

show abstract

“…To identify eligible minorities, we used Medicare race codes (MRC), geo-coding algorithms and the Census-based Spanish surname list [21][22][23] to identify subjects having a high probability of being Hispanic or nonHispanic blacks. The accuracy of this algorithm was 91 % for the identification of black subjects and 92 % for Hispanic subjects.…”

Section: Inclusion/exclusion Criteriamentioning

confidence: 99%

Can Phone-Based Motivational Interviewing Improve Medication Adherence to Antiplatelet Medications After a Coronary Stent Among Racial Minorities? A Randomized Trial

et al. 2014

View full text Add to dashboard Cite

BACKGROUND:Minorities have lower adherence to cardiovascular medications and have worst cardiovascular outcomes post coronary stent placement OBJECTIVE: The aim of this study is to compare the efficacy of phone-delivered Motivational Interviewing (MINT) to an educational video at improving adherence to antiplatelet medications among insured minorities. DESIGN: This was a randomized study. PARTICIPANTS: We identified minorities with a recently placed coronary stent from an administrative data set by using a previously validated algorithm. INTERVENTIONS: MINT subjects received quarterly phone calls and the DVD group received a one-time mailed video. MAIN MEASURES: Outcome variables were collected at baseline and at 12-month post-stent, using surveys and administrative data. The primary outcome was antiplatelet (clopidogrel and prasugrel) adherence measured by Medication Possession Ratio (MPR) and self-reported adherence (Morisky score). We also measured appropriate adherence defined as an MPR ≥ 0.80. KEY RESULTS: We recruited 452 minority subjects with a new coronary stent (44 % Hispanics and 56 % Black). The patients had a mean age of 69.5±8.8, 58 % were males, 78 % had an income lower than $30,000 per year and only 22 % had achieved high school education or higher. The MPR for antiplatelet medications was 0.77 for the MINT group compared to 0.70 for the DVD group (p<0.05). The percentage of subjects with adequate adherence to their antiplatelet medication was 64 % in the MINT group and 50 % in the DVD group (p<0.01). Self-reported adherence at 12 months was higher in the MINT group compared to the DVD group (p<0.01). Results were similar among drug-eluting stent (DES) recipients. CONCLUSIONS: Among racial minorities, a phone-based motivational interview is effective at improving adherence to antiplatelet medications post coronary stent placement. Phone-based MINT seems to be a promising and cost-effective strategy to modify risk behaviors among minority populations at high cardiovascular risk. BACKGROUNDThe safe use of coronary stents requires the daily use of thienopyridines for 3 to 12 months after percutaneous coronary intervention (PCI). 1 The premature discontinuation of these medications 1 is associated with an increased risk of instent thrombosis, cardiovascular events and death. 2-6 Unfortunately, lack of medication adherence is common and is associated with significant health care costs and mortality. 7,8 Vulnerable groups such as racial minorities and the elderly have a higher risk of poor adherence. 5,6,9,10 In the case of antiplateletet medications, blacks are more likely to not receive a clopidogrel prescription 11 or to not fill it after PCI. Further, our prior analyses of insurer claims data showed that minority populations were less adherent to antiplatelet medications post drug-eluting stent (DES) placement. 12 The lack of appropriate use of evidence-based therapies after PCI may partially contribute to the excess morbidity and mortality reported among minorities. 13,14,6 The improvement of med...

show abstract

“…To calculate P(R|S, L), we follow a well-developed health care literature and use Bayes' rule (Elliott et al 2008(Elliott et al , 2009Fiscella and Fremont 2006;Imai and Khanna 2016). 7 This approach provides us a "probabilistic prediction of individual [race or] ethnicity" (Imai and Khanna 2016: 265) for a given surname in a geographic area.…”

Section: Data and Resultsmentioning

confidence: 99%

“…This is because last names can signal different races in different places. Elliott et al (2009) provide a couple of powerful examples for which this is the case.…”

Section: Last Name Selectionmentioning

confidence: 96%

Last Name Selection in Audit Studies

Crabtree¹,

Chykina²

2018

SocScience

View full text Add to dashboard Cite

Abstract:In this article, we build on Gaddis (2017a) by illuminating a key variable plausibly related to racial perceptions of last names-geography. We show that the probability that any individual belongs to a race is conditional not only on their last name but also on surrounding racial demographics. Specifically, we demonstrate that the probability of a name denoting a race varies considerably across contexts, and this is more of a problem for some names than others. This result has two important implications for audit study research: it suggests important limitations for (1) the generalizability of audit study findings and (2) for the interpretation of geography-based conditional effects. This means that researchers should be careful to select names that consistently signal racial groups regardless of local demographics. We provide a slim R package that can help researchers do this.

show abstract

Using the Census Bureau’s surname list to improve estimates of race/ethnicity and associated disparities

Cited by 201 publications

References 12 publications

Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records

Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records

Can Phone-Based Motivational Interviewing Improve Medication Adherence to Antiplatelet Medications After a Coronary Stent Among Racial Minorities? A Randomized Trial

Last Name Selection in Audit Studies

Contact Info

Product

Resources

About