Daniel B McArtor
Biographic Data
| ID | 5761081 |
|---|---|
| NAME | Daniel B McArtor |
| GIVEN NAMES | Daniel B |
| FAMILY NAME | McArtor |
| SIGNATURE | MCARTOR D B |
| AFFILIATIONS | University of Notre Dame |
| ORCID | 0000-0003-3065-7014 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2018 |
| H-INDEX | 0 |
Genetic and environmental contributions to the development of childhood aggression
Longitudinal data from a large sample of twins participating in the Netherlands Twin Register (n = 42,827, age range 3-16) were analyzed to investigate the genetic and environmental contributions to childhood aggression. Genetic auto-regressive (simplex) models were used to assess whether the same genes are involved or whether new genes come into play as children grow up. The authors compared 2 different simplex models to disentangle potentially …
A Gradient-Boosting Machine for Hierarchically Clustered Data
"A Gradient-Boosting Machine for Hierarchically Clustered Data." Multivariate Behavioral Research, 52(1), p. 117
No prominent works on this page.
A Gradient-Boosting Machine for Hierarchically Clustered Data
"A Gradient-Boosting Machine for Hierarchically Clustered Data." Multivariate Behavioral Research, 52(1), p. 117
Genetic and environmental contributions to the development of childhood aggression
Longitudinal data from a large sample of twins participating in the Netherlands Twin Register (n = 42,827, age range 3-16) were analyzed to investigate the genetic and environmental contributions to childhood aggression. Genetic auto-regressive (simplex) models were used to assess whether the same genes are involved or whether new genes come into play as children grow up. The authors compared 2 different simplex models to disentangle potentially …
Advanced Clustering Algorithms Research (1 work) · Aggression (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Bayesian Methods and Mixture Models (1 work) · Behavioural genetics (1 work) · Boosting (machine learning) (1 work) · Bullying, Victimization, and Aggression (1 work) · Child and Adolescent Psychosocial and Emotional Development (1 work) · Cognitive Abilities and Testing (1 work)