Objectives. We examined whether kindergarten teachers' ratings of children’s prosocial skills, an indicator of noncognitive ability at school entry, predict key adolescent and adult outcomes. Our goal was to determine unique associations over and above other important child, family, and contextual characteristics.Methods. Data came from the Fast Track study of low–socioeconomic status neighborhoods in 3 cities and 1 rural setting. We assessed associations between measured outcomes in kindergarten and outcomes 13 to 19 years later (1991–2000). Models included numerous control variables representing characteristics of the child, family, and context, enabling us to explore the unique contributions among predictors.Results. We found statistically significant associations between measured social-emotional skills in kindergarten and key young adult outcomes across multiple domains of education, employment, criminal activity, substance use, and mental health.Conclusions. A kindergarten measure of social-emotiona...

Early Social-Emotional Functioning and Public Health: The Relationship Between Kindergarten Social Competence and Future Wellness

Missing data (a) reside at three missing data levels of analysis (item-, construct-, and person-level), (b) arise from three missing data mechanisms (missing completely at random, missing at random...

Missing Data Five Practical Guidelines

Mediation analyses abound in social and personality psychology. Current recommendations for assessing power and sample size in mediation models include using a Monte Carlo power analysis simulation and testing the indirect effect with a bootstrapped confidence interval. Unfortunately, these methods have rarely been adopted by researchers due to limited software options and the computational time needed. We propose a new method and convenient tools for determining sample size and power in mediation models. We demonstrate our new method through an easy-to-use application that implements the method. These developments will allow researchers to quickly and easily determine power and sample size for simple and complex mediation models.

Determining Power and Sample Size for Simple and Complex Mediation Models

This study illustrates an overarching psychometric approach of broad relevance to investigations of 2 sources of construct-relevant psychometric multidimensionality present in many complex multidimensional instruments routinely used in psychological and educational research. These 2 sources of construct-relevant psychometric multidimensionality are related to (a) the fallible nature of indicators as perfect indicators of a single construct, and (b) the hierarchical nature of the constructs being assessed. The first source is identified by comparing confirmatory factor analytic (CFA) and exploratory structural equation modeling (ESEM) solutions. The second source is identified by comparing first-order, hierarchical, and bifactor measurement models. To provide an applied illustration of the substantive relevance of this framework, we first apply these models to a sample of German children (N = 1,957) who completed the Self-Description Questionnaire (SDQ–I). Then, in a second study using a simulated data set...

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A Bifactor Exploratory Structural Equation Modeling Framework for the Identification of Distinct Sources of Construct-Relevant Psychometric Multidimensionality

The metaSEM package provides functions to conduct univariate, multivariate, and three-level meta-analyses using a structural equation modeling (SEM) approach via the \texttt{OpenMx} package in R statistical platform. It also implements the two-stage SEM approach to conducting fixed- and random-effects meta-analytic SEM on correlation or covariance matrices. This paper briefly outlines the theories and their implementations. It provides a summary on how meta-analyses can be formulated as structural equation models. The paper closes with a conclusion on several relevant topics to this SEM-based meta-analysis. Several examples are used to illustrate the procedures in the supplementary material.

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metaSEM: an R package for meta-analysis using structural equation modeling.

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Sabrina Eberhart

Papers

Applied Missing Data Analysis