Philippe Rast
Biographic Data
| ID | 5760085 |
|---|---|
| NAME | Philippe Rast |
| GIVEN NAMES | Philippe |
| FAMILY NAME | Rast |
| SIGNATURE | RAST P |
| AFFILIATIONS | University of California System |
| ORCID | 0000-0003-3630-6629 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 4 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Enhancing generalizability theory with mixed‐effects models for heteroscedasticity in psychological measurement
Generalizability theory (G‐theory) defines a statistical framework for assessing measurement reliability by decomposing observed variance into meaningful components attributable to persons, facets, and error. Classic G‐theory assumes homoscedastic residual variances across measurement conditions, an assumption that is often violated in psychological and behavioural data. The main focus of this work is to extend G‐theory using a mixed‐effects loca…
A Network Analysis of Executive Functions in Children and Adolescents With and Without Attention-Deficit/Hyperactivity Disorder
The unity and diversity of executive functions
As a novel approach to conceptualizing executive functions, this study applied network analysis to a common battery of executive function tests administered to a sample covering the life span. Participants (N = 3,944; age: M = 20.8 years, SD = 19.6, range: 3-85; maternal/self education: M = 12.9 years, SD = 2.6; 53.3% girls/women, 46.7% boys/men; 61.1% White, 18.2% African American, 14.0% Latinx, 6.8% other races/ethnicities) completed tests of i…
On Nonregularized Estimation of Psychological Networks
An important goal for psychological science is developing methods to characterize relationships between variables. Customary approaches use structural equation models to connect latent factors to a number of observed measurements, or test causal hypotheses between observed variables. More recently, regularized partial correlation networks have been proposed as an alternative approach for characterizing relationships among variables through off-di…
A Mixed-Effects Location Scale Model for Dyadic Interactions
We present a mixed-effects location scale model (MELSM) for examining the daily dynamics of affect in dyads. The MELSM includes person and time-varying variables to predict the location, or individual means, and the scale, or within-person variances. It also incorporates a submodel to account for between-person variances. The dyadic specification can accommodate individual and partner effects in both the location and the scale components, and all…
The unity and diversity of executive functions
Modeling Individual Differences in Within-Person Variation of Negative and Positive Affect in a Mixed Effects Location Scale Model Using Bugs/Jags
A mixed effects location scale model was used to model and explain individual differences in within-person variability of negative and positive affect across 7 days (N=178) within a measurement burst design. The data come from undergraduate university students and are pooled from a study that was repeated at two consecutive years. Individual differences in level and change in mood was modeled with a random intercept and random slope where the res…
Verbal knowledge, working memory, and processing speed as predictors of verbal learning in older adults
The present study aimed at modeling individual differences in a verbal learning task by means of a latent structured growth curve approach based on an exponential function that yielded 3 parameters: initial recall, learning rate, and asymptotic performance. Three cognitive variables-speed of information processing, verbal knowledge, working memory-and the participant's age were included in the model in order to explain individual differences in t…
The unity and diversity of executive functions
As a novel approach to conceptualizing executive functions, this study applied network analysis to a common battery of executive function tests administered to a sample covering the life span. Participants (N = 3,944; age: M = 20.8 years, SD = 19.6, range: 3-85; maternal/self education: M = 12.9 years, SD = 2.6; 53.3% girls/women, 46.7% boys/men; 61.1% White, 18.2% African American, 14.0% Latinx, 6.8% other races/ethnicities) completed tests of i…
Verbal knowledge, working memory, and processing speed as predictors of verbal learning in older adults
The present study aimed at modeling individual differences in a verbal learning task by means of a latent structured growth curve approach based on an exponential function that yielded 3 parameters: initial recall, learning rate, and asymptotic performance. Three cognitive variables-speed of information processing, verbal knowledge, working memory-and the participant's age were included in the model in order to explain individual differences in t…
Modeling Individual Differences in Within-Person Variation of Negative and Positive Affect in a Mixed Effects Location Scale Model Using Bugs/Jags
A mixed effects location scale model was used to model and explain individual differences in within-person variability of negative and positive affect across 7 days (N=178) within a measurement burst design. The data come from undergraduate university students and are pooled from a study that was repeated at two consecutive years. Individual differences in level and change in mood was modeled with a random intercept and random slope where the res…
A Mixed-Effects Location Scale Model for Dyadic Interactions
We present a mixed-effects location scale model (MELSM) for examining the daily dynamics of affect in dyads. The MELSM includes person and time-varying variables to predict the location, or individual means, and the scale, or within-person variances. It also incorporates a submodel to account for between-person variances. The dyadic specification can accommodate individual and partner effects in both the location and the scale components, and all…
The unity and diversity of executive functions
On Nonregularized Estimation of Psychological Networks
An important goal for psychological science is developing methods to characterize relationships between variables. Customary approaches use structural equation models to connect latent factors to a number of observed measurements, or test causal hypotheses between observed variables. More recently, regularized partial correlation networks have been proposed as an alternative approach for characterizing relationships among variables through off-di…
The unity and diversity of executive functions
As a novel approach to conceptualizing executive functions, this study applied network analysis to a common battery of executive function tests administered to a sample covering the life span. Participants (N = 3,944; age: M = 20.8 years, SD = 19.6, range: 3-85; maternal/self education: M = 12.9 years, SD = 2.6; 53.3% girls/women, 46.7% boys/men; 61.1% White, 18.2% African American, 14.0% Latinx, 6.8% other races/ethnicities) completed tests of i…
A Network Analysis of Executive Functions in Children and Adolescents With and Without Attention-Deficit/Hyperactivity Disorder
Enhancing generalizability theory with mixed‐effects models for heteroscedasticity in psychological measurement
Generalizability theory (G‐theory) defines a statistical framework for assessing measurement reliability by decomposing observed variance into meaningful components attributable to persons, facets, and error. Classic G‐theory assumes homoscedastic residual variances across measurement conditions, an assumption that is often violated in psychological and behavioural data. The main focus of this work is to extend G‐theory using a mixed‐effects loca…
Mental Health Research Topics (5 works) · Developmental psychology (4 works) · Psychology (4 works) · Cognition (3 works) · Functional Brain Connectivity Studies (3 works) · Working memory (3 works) · Clinical Psychology (2 works) · Cognitive psychology (2 works) · Correlation (2 works) · Executive functions (2 works)