A5043821244- Mental Health Research Topics
- Functional Brain Connectivity Studies
- Complex Network Analysis Techniques
- Psychometric Methodologies and Testing
- Statistical Methods and Bayesian Inference
- Child and Animal Learning Development
- Cognitive Abilities and Testing
- Advanced Causal Inference Techniques
- Advanced Statistical Modeling Techniques
- Language Development and Disorders
- Optimal Experimental Design Methods
- Behavioral Health and Interventions
- Statistical Methods and Inference
- Early Childhood Education and Development
- Genetic Associations and Epidemiology
- Neuroendocrine regulation and behavior
- Child and Adolescent Psychosocial and Emotional Development
- EEG and Brain-Computer Interfaces
- Neural and Behavioral Psychology Studies
- Stress Responses and Cortisol
- Bayesian Modeling and Causal Inference
- scientometrics and bibliometrics research
- Tryptophan and brain disorders
- Genetic and phenotypic traits in livestock
- Cognitive Science and Mapping
University of California, Davis
2016-2025
University of Amsterdam
2013-2018
Amsterdam University of the Arts
2016
University of Kansas
2011-2013
University of British Columbia
2007-2013
The University of Texas at Austin
2010-2011
University of Alberta
2003
A simulation study compared the performance of robust normal theory maximum likelihood (ML) and categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 2-7 categories, 4 sample sizes, latent distributions, 5 patterns category thresholds. Results revealed that loadings standard errors generally most accurately estimated using cat-LS, especially fewer than categories; however, correlations model fit...
In recent years, network analysis has been applied to identify and analyse patterns of statistical association in multivariate psychological data. these approaches, nodes represent variables a data set, edges pairwise conditional associations between the data, while conditioning on remaining variables. This Primer provides an anatomy techniques, describes current state art discusses open problems. We relevant structures which may be applied: cross-sectional repeated measures intensive...
Despite the widespread and rising popularity of structural equation modeling (SEM) in psychology, there is still much confusion surrounding how to choose an appropriate sample size for SEM. Currently available guidance primarily consists sample-size rules thumb that are not backed up by research power analyses detecting model misspecification. Missing from most current practices analysis a target effect (e.g., regression coefficient between latent variables). In this article, we (a)...
Although current classification systems have greatly contributed to the reliability of psychiatric diagnoses, they ignore unique role individual symptoms and, consequently, potentially important information is lost. The network approach, in contrast, assumes that psychopathology results from causal interplay between and focuses specifically on these their complex associations. By using a sophisticated analysis technique, this study constructed an empirically based structure 120 twelve major...
Abstract Planned missing data designs allow researchers to collect incomplete from participants by randomly assigning have items on a survey (multiform designs) or measurement occasions in longitudinal design (wave administering an intensive measure small subsample of larger dataset (two‐method designs). When these are implemented correctly and when missingness is dealt with using modern approach, the cost collection lowered (sometimes dramatically) reduced participant burden may result...
Previous research and methodological advice has focused on the importance of accounting for measurement error in psychological data. That perspective assumes that variables conform to a common factor model. We explore what happens when data are not generated from model nonetheless modeled as reflecting factor. Through series hypothetical examples an empirical reanalysis, we show is misused, structural parameter estimates indicate relations among constructs can be severely biased. Moreover,...
It is common practice in correlational or quasiexperimental studies to use statistical control remove confounding effects from a regression coefficient. Controlling for relevant confounders can debias the estimated causal effect of predictor on an outcome; that is, it bring coefficient closer value true effect. But works only under ideal circumstances. When selected variables are inappropriate, controlling result estimates more biased than uncontrolled estimates. Despite ubiquity published...
Abstract Event‐related potentials (ERPs) can be very noisy, and yet, there is no widely accepted metric of ERP data quality. Here, we propose a universal measure quality for research—the standardized measurement error (SME) —which special case the standard measurement. Whereas some existing metrics provide generic quantification noise level, SME quantifies (precision) specific amplitude or latency value being measured in given study (e.g., peak P3 wave). It applied to virtually any that...
An important goal for psychological science is developing methods to characterize relationships between variables. Customary approaches use structural equation models connect latent factors a number of observed measurements, or test causal hypotheses More recently, regularized partial correlation networks have been proposed as an alternative approach characterizing among variables through off-diagonal elements in the precision matrix. While graphical Lasso (glasso) has emerged default...
Network theory and accompanying methodology are becoming increasingly popular as an alternative to latent variable models for representing and, ultimately, understanding psychological constructs. The core feature of network is that individual observed items (e.g., symptoms depression) allowed directly influence each other, resulting in interconnected system items. dynamics such a give rise emergent states constructs depressive episode). modeling has been applied cross-sectional data...
Recent research in behavioral genetics has found evidence for a Gene × Environment interaction on cognitive ability: Individual differences ability among children raised socioeconomically advantaged homes are primarily due to genes, whereas environmental factors more influential from disadvantaged homes. We investigated the developmental origins of this sample 750 pairs twins measured Bayley Short Form test infant mental ability, once at age 10 months and again 2 years. A was evident...
Networks are gaining popularity as an alternative to latent variable models for representing psychological constructs. Whereas approaches introduce unobserved common causes explain the relations among observed variables, network posit direct causal between variables. While these lead radically different understandings of constructs interest, recent articles have established mathematical equivalences that hold and models. We argue fact any model from one class there is equivalent other does...
Though religion has been shown to have generally positive effects on normative 'prosocial' behavior, recent laboratory research suggests that these may be driven primarily by supernatural punishment. Supernatural benevolence, the other hand, actually associated with less prosocial behavior. Here, we investigate at societal level, showing proportion of people who believe in hell negatively predicts national crime rates whereas belief heaven higher rates. These remain after accounting for a...
Health-Related Quality of Life (HRQoL) research has typically adopted either a formative approach, in which HRQoL is the common effect its observables, or reflective approach--defining as latent variable that determines observable characteristics HRQoL. Both approaches, however, do not take into account complex organization these characteristics. The objective this study was to introduce new approach for analyzing data, namely network model (NM). An NM, opposed traditional strategies,...
Because indirect measures of personality self–concepts such as the Implicit Association Test (IAT) allow tapping into automatic processes, they can offer advantages over self–report measures. However, prior investigations have led to mixed results regarding validity conscientiousness. We suggest that these might be due a failure consider different facets These are crucial importance because associated differentially with other psychobiological constructs and also characterized by mechanisms....
To deal with missing data that arise due to participant nonresponse or attrition, methodologists have recommended an "inclusive" strategy where a large set of auxiliary variables are used inform the process. In practice, possible is often too large. We propose using principal components analysis (PCA) reduce number manageable number. A series Monte Carlo simulations compared performance inclusive eight (inclusive approach) PCA just one component derived from original (PCA approach). examined...
Recent research has suggested that a range of psychological disorders may stem from single underlying common factor, which been dubbed the p-factor. This finding spur line in psychopathology very similar to history factor modeling intelligence and, more recently, personality research, general factors have proposed. We point out some risks and interpreting factors, derived fields research. argue that: (a) factor-analytic resolution, i.e., convergence literature on particular structure, should...