Benjamin Domingue
Biographic Data
| ID | 6045588 |
|---|---|
| NAME | Benjamin Domingue |
| GIVEN NAMES | Benjamin |
| FAMILY NAME | Domingue |
| SIGNATURE | DOMINGUE B |
| AFFILIATIONS | Stanford University |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 3 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 1 |
Using Machine Learning to Advance Early Warning Systems
Background/Context Early warning indicators (EWI) are often used by states and districts to identify students who are not on track to finish high school, and provide supports/interventions to increase the odds the student will graduate. While EWI are diverse in terms of the academic behaviors they capture, research suggests that indicators like course failures, chronic absenteeism, and suspensions can help identify students in need of additional …
Interactions between Polygenic Scores and Environments
Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data-in particular, polygenic scores-in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key cha…
New Evidence of Skin Color Bias and Health Outcomes Using Sibling Difference Models
In this research note, we use data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to determine whether darker skin tone predicts hypertension among siblings using a family fixed-effects analytic strategy. We find that even after we account for common family background and home environment, body mass index, age, sex, and outdoor activity, darker skin color significantly predicts hypertension incidence among sibling…
Conceptualizing School Belongingness in Native Youth
The Psychological Sense of School Membership (PSSM) scale is widely used to measure school belongingness among adolescents. However, previous studies identify inconsistencies in factor structures across different populations. The factor structure of the PSSM has yet to be examined with American Indian/Alaska Native (AI/AN) youth, a population of keen interest given reports of their educational and health disparities, and the potential of belongin…
The Genetics of Success
A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study ( N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and en…
New Evidence of Skin Color Bias and Health Outcomes Using Sibling Difference Models
In this research note, we use data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to determine whether darker skin tone predicts hypertension among siblings using a family fixed-effects analytic strategy. We find that even after we account for common family background and home environment, body mass index, age, sex, and outdoor activity, darker skin color significantly predicts hypertension incidence among sibling…
The Genetics of Success
A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study ( N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and en…
Conceptualizing School Belongingness in Native Youth
The Psychological Sense of School Membership (PSSM) scale is widely used to measure school belongingness among adolescents. However, previous studies identify inconsistencies in factor structures across different populations. The factor structure of the PSSM has yet to be examined with American Indian/Alaska Native (AI/AN) youth, a population of keen interest given reports of their educational and health disparities, and the potential of belongin…
New Evidence of Skin Color Bias and Health Outcomes Using Sibling Difference Models
In this research note, we use data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to determine whether darker skin tone predicts hypertension among siblings using a family fixed-effects analytic strategy. We find that even after we account for common family background and home environment, body mass index, age, sex, and outdoor activity, darker skin color significantly predicts hypertension incidence among sibling…
Using Machine Learning to Advance Early Warning Systems
Background/Context Early warning indicators (EWI) are often used by states and districts to identify students who are not on track to finish high school, and provide supports/interventions to increase the odds the student will graduate. While EWI are diverse in terms of the academic behaviors they capture, research suggests that indicators like course failures, chronic absenteeism, and suspensions can help identify students in need of additional …
Interactions between Polygenic Scores and Environments
Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data-in particular, polygenic scores-in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key cha…
Psychology (5 works) · Computer Science (3 works) · Demography (3 works) · Developmental psychology (3 works) · Sociology (3 works) · Artificial Intelligence (2 works) · Clinical Psychology (2 works) · Machine learning (2 works) · Population (2 works) · Advanced Causal Inference Techniques (1 work)