Reducing Attenuation Bias in Regression Analyses Involving Rating Scale Data via Psychometric Modeling

Many studies in fields such as psychology and educational sciences obtain information about attributes of subjects through observational studies, in which raters score subjects using multiple-item rating scales. Error variance due to measurement effects, such as items and raters, attenuate the regression coefficients and lower the power of (hierarchical) linear models. A modeling procedure is discussed to reduce the attenuation. The procedure consists of (1) an item response theory (IRT) model to map the discrete item responses to a continuous latent scale and (2) a generalizability theory (GT) model to separate the variance in the latent measurement into variance components of interest and nuisance variance components. It will be shown how measurements obtained from this mixture of IRT and GT models can be embedded in (hierarchical) linear models, both as predictor or criterion variables, such that error variance due to nuisance effects are partialled out. Using examples from the field of educational measurement, it is shown how general-purpose software can be used to implement the modeling procedure.</p

On the Joys of Missing Data

We provide conceptual introductions to missingness mechanisms—missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR)—and state-of-the-art methods of handling missing data—full-information maximum likelihood (FIML) and multiple imputation (MI)—followed by a discussion of planned missing designs: multiform questionnaire protocols, two-method measurement models, and wave-missing longitudinal designs. We reviewed 80 articles of empirical studies published in the 2012 issues of the Journal of Pediatric Psychology to present a picture of how adequately missing data are currently handled in this field. To illustrate the benefits of utilizing MI or FIML and incorporating planned missingness into study designs, we provide example analyses of empirical data gathered using a three-form planned missing design

Corrigendum: Determinants of Non-paid Task Division in Gay-, Lesbian-, and Heterosexual-Parent Families With Infants Conceived Using Artificial Reproductive Techniques.

[This corrects the article DOI: 10.3389/fpsyg.2020.00914.]

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P <5 x 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.Peer reviewe

IMPS 2019 symposium: The lavaan ecosystem

Files associated with a symposium about R packages that extend the functionality of the lavaan packag

A Social Relations Model of Self- and Peer-Perceived Body Preoccupation: Modeling Missing Data in a Partially Observed Network

This was part of a symposium on practical applications of Bayesian modeling. Other presenters included Mauricio Garnier-Villarreal and Graham Rifenbark. Our materials (example data, R syntax, slides) can be downloaded from my OSF account: https://osf.io/fmhg6

Extending Structural Equation Models of Generalizability Theory

R syntax to replicate analyses in the article: How to Estimate Absolute-Error Components in Structural Equation Models of Generalizability Theory

Comparing Analytic Strategies for Dependent-Sample Means Using Real and Simulated Data

Four general frameworks (GLM/ANOVA, SEM, MLM, GEE) for testing hypotheses about dependent-sample (e.g., repeated-measures) means are compared using (a) real data to demonstrate how methods can be applied in R and SPSS and (b) simulated data to reveal which methods are most powerful while maintaining nominal Type I error rates across a variety of conditions

APS 2017 Symposium: Bayesian Methods

Symposium: Modeling Real-World Complexity Using Bayesian Method