Empirical Bayes Priors for MCMC Estimation of the Multivariate Social Relations Model.

The social relations model (SRM) is a linear random-effects model applied to examine dyadic round-robin data within social networks. Such data have a unique multilevel structure in that dyads are cross-classified within individuals who may be nested within different social networks. The SRM decomposes perceptual or behavioral measures into multiple components: case-level random effects (in-coming and out-going effects) and dyad-level residuals (relationship effects), the associations among which are often of substantive interest.

How to Estimate Intraclass Correlation Coefficients for Interrater Reliability from Planned Incomplete Data.

The interrater reliability (IRR) of observational data is often estimated by means of intraclass correlation coefficients (ICCs), which are flexible IRR estimators that are based on the variance decomposition of scores obtained by observations. ICCs are typically estimated using mean squares from an ANOVA model, the computation of which is not straightforward for incomplete data. However, many studies in behavioral research use planned missing observational designs, in which the raters partially vary across subjects.

A tutorial on estimating dynamic treatment regimes from observational longitudinal data using lavaan.

Psychological and behavioral scientists develop interventions toward addressing pressing societal challenges. But such endeavors are complicated by treatments that change over time as individuals' needs and responses evolve. For instance, students initially in a multiyear mentoring program to improve future academic outcomes may not continue with the program after interim school engagement improves.

Interrater Reliability for Interdependent Social Network Data: A Generalizability Theory Approach.

We propose interrater reliability coefficients for observational interdependent social network data, which are dyadic data from a network of interacting subjects that are observed by external raters. Using the social relations model, dyadic scores of subjects' behaviors during these interactions can be decomposed into actor, partner, and relationship effects. These effects constitute different facets of theoretical interest about which researchers formulate research questions.

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.

Intervention-induced temperament changes in children: Evidence from a randomized controlled trial of the Incredible Years parent program.

Child temperament has long been viewed as a potential susceptibility factor in the link between parenting and child disruptive behavior (CDB). Specifically, the idea is that children with higher negative emotionality, surgency, and lower effortful control are more affected by their received parenting, but experimental evidence is scarce. Also, others have argued that child temperament might not be a susceptibility factor but a factor that can change through parents' participation in a parenting intervention.

Parental socialization of guilt and shame in early childhood.

Self-conscious emotions emerge early in human development and they help children navigate social relationships. Little is known about the socialization of self-conscious emotions in early childhood. We theorized that parental mental state language use and warmth would be important for young children's self-conscious emotions and their consequent prosocial behaviors.

Autistic traits and self-conscious emotions in early childhood.

Self-conscious emotions arise from evaluating the self through the eyes of others. Given that children with autistic traits may experience difficulties with understanding others' minds, they might show less attuned self-conscious emotions. Two-to-five-year-old children's (N = 98, M  = 48.

Power analysis for conditional indirect effects: A tutorial for conducting Monte Carlo simulations with categorical exogenous variables.

Conceptual and statistical models that include conditional indirect effects (i.e., so-called "moderated mediation" models) are increasingly popular in the behavioral sciences.

Updated guidelines on selecting an intraclass correlation coefficient for interrater reliability, with applications to incomplete observational designs.

Several intraclass correlation coefficients (ICCs) are available to assess the interrater reliability (IRR) of observational measurements. Selecting an ICC is complicated, and existing guidelines have three major limitations. First, they do not discuss incomplete designs, in which raters partially vary across subjects.

Assessing measurement invariance with moderated nonlinear factor analysis using the R package OpenMx.

Assessing measurement invariance is an important step in establishing a meaningful comparison of measurements of a latent construct across individuals or groups. Most recently, moderated nonlinear factor analysis (MNLFA) has been proposed as a method to assess measurement invariance. In MNLFA models, measurement invariance is examined in a single-group confirmatory factor analysis model by means of parameter moderation.

Interrater reliability for multilevel data: A generalizability theory approach.

Current interrater reliability (IRR) coefficients ignore the nested structure of multilevel observational data, resulting in biased estimates of both subject- and cluster-level IRR. We used generalizability theory to provide a conceptualization and estimation method for IRR of continuous multilevel observational data. We explain how generalizability theory decomposes the variance of multilevel observational data into subject-, cluster-, and rater-related components, which can be estimated using Markov chain Monte Carlo (MCMC) estimation.

Analytical power calculations for structural equation modeling: A tutorial and Shiny app.

Conducting a power analysis can be challenging for researchers who plan to analyze their data using structural equation models (SEMs), particularly when Monte Carlo methods are used to obtain power. In this tutorial, we explain how power calculations without Monte Carlo methods for the χ test and the RMSEA tests of (not-)close fit can be conducted using the Shiny app "power4SEM". power4SEM facilitates power calculations for SEM using two methods that are not computationally intensive and that focus on model fit instead of the statistical significance of (functions of) parameters.

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.

Dopamine Functioning and Child Externalizing Behavior: A Longitudinal Analysis of Polygenic Susceptibility to Parenting.

Objective: This study investigated how genetic susceptibility may affect children's sensitivity to parenting practices in their development of externalizing behavior. We created a continuous polygenic index composed of 5 dopamine polymorphisms to investigate the moderating role of dopamine-related genes in shaping parent-child gene-by-environment (Gc×E) interactions. Accumulating research supports that differences in children's dopamine neurotransmission make certain children more susceptible to both negative and positive parenting practices, a "for-better and for-worse" effect.

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

The division of non-paid labor in heterosexual parents in the West is usually still gender-based, with mothers taking on the majority of direct caregiving responsibilities. However, in same-sex couples, gender cannot be the deciding factor. Inspired by Feinberg's ecological model of co-parenting, this study investigated whether infant temperament, parent factors (biological relatedness to child, psychological adjustment, parenting stress, and work status), and partner relationship quality explained how first-time gay, lesbian, and heterosexual parents divided labor (childcare and family decision-making) when their infants were 4 and 12 months old.

Self-Reports and Caregivers' Proxy Reports of Unmet Needs of Persons With Dementia: Implications for Both Partners' Health-Related Quality of Life.

Objective: This study examined in a large sample of dementia caregiving dyads the associations between both partners' reports of unmet needs in persons with dementia (PwDs) and both partners' health-related quality of life (HRQOL).

Methods: This was a cross-sectional self-report survey of 521 community-dwelling dyads in a pragmatic trial in the Netherlands. The Camberwell Needs Assessment was used to measure PwDs' unmet needs.

A multiple imputation score test for model modification in structural equation models.

Structural equation modeling (SEM) applications routinely employ a trilogy of significance tests that includes the likelihood ratio test, Wald test, and score test or modification index. Researchers use these tests to assess global model fit, evaluate whether individual estimates differ from zero, and identify potential sources of local misfit, respectively. This full cadre of significance testing options is not yet available for multiply imputed data sets, as methodologists have yet to develop a general score test for this context.

Adapting fit indices for Bayesian structural equation modeling: Comparison to maximum likelihood.

In a frequentist framework, the exact fit of a structural equation model (SEM) is typically evaluated with the chi-square test and at least one index of approximate fit. Current Bayesian SEM (BSEM) software provides one measure of overall fit: the posterior predictive p value (PPP χ2 ). Because of the noted limitations of PPP χ2 , common practice for evaluating Bayesian model fit instead focuses on model comparison, using information criteria or Bayes factors.

Using restricted factor analysis to select anchor items and detect differential item functioning.

Restricted factor analysis (RFA) is a powerful method to test for uniform differential item functioning (DIF), but it may require empirically selecting anchor items to prevent inflated Type I error rates. We conducted a simulation study to compare two empirical anchor-selection strategies: a one-step rank-based strategy and an iterative selection procedure. Unlike the iterative procedure, the rank-based strategy had a low risk and degree of contamination within the empirically selected anchor set, even with small samples.

Permutation randomization methods for testing measurement equivalence and detecting differential item functioning in multiple-group confirmatory factor analysis.

In multigroup factor analysis, different levels of measurement invariance are accepted as tenable when researchers observe a nonsignificant (Δ)χ2 test after imposing certain equality constraints across groups. Large samples yield high power to detect negligible misspecifications, so many researchers prefer alternative fit indices (AFIs). Fixed cutoffs have been proposed for evaluating the effect of invariance constraints on change in AFIs (e.

Relating Measurement Invariance, Cross-Level Invariance, and Multilevel Reliability.

Data often have a nested, multilevel structure, for example when data are collected from children in classrooms. This kind of data complicate the evaluation of reliability and measurement invariance, because several properties can be evaluated at both the individual level and the cluster level, as well as across levels. For example, cross-level invariance implies equal factor loadings across levels, which is needed to give latent variables at the two levels a similar interpretation.