The : A practical guide for the application of meta-analyses to clinical cases.

Despite efforts to incorporate evidence-based practice into mental health settings, there has been inconsistent success doing so. Several barriers to the implementation of evidence-based practice have been identified, including limitations in time and statistical training. One promising approach to further bridge the science-practice gap is the greater use of meta-analytic studies to clarify the magnitude of treatment effects and to understand components of treatments that are more effective within specific populations.

Caregiver Report of Children's Exposure to Adverse Life Events: Concordance Between Questionnaire and Interview Approaches.

Assessment practices for measuring adverse life events (ALEs) are often characterized by considerable variability, which is associated with inconsistency and reproducibility issues when conducting research on children with ALE exposure. One aspect of assessment variability for caregiver report of children's ALE history that has received minimal attention is assessment format. To address this issue, the current study evaluated concordance between two main ALE assessment formats: interviews and questionnaires.

Growth Modeling in a Diagnostic Classification Model (DCM) Framework-A Multivariate Longitudinal Diagnostic Classification Model.

A multivariate longitudinal DCM is developed that is the composite of two components, the log-linear cognitive diagnostic model (LCDM) as the measurement model component that evaluates the mastery status of attributes at each measurement occasion, and a generalized multivariate growth curve model that describes the growth of each attribute over time. The proposed model represents an improvement in the current longitudinal DCMs given its ability to incorporate both balanced and unbalanced data and to measure the growth of a single attribute directly without assuming that attributes grow in the same pattern. One simulation study was conducted to evaluate the proposed model in terms of the convergence rates, the accuracy of classification, and parameter recoveries under different combinations of four design factors: the sample size, the growth patterns, the G matrix design, and the number of measurement occasions.

Using Bayesian Nonparametric Item Response Function Estimation to Check Parametric Model Fit.

Previous studies indicated that the assumption of logistic form of parametric item response functions (IRFs) is violated often enough to be worth checking. Using nonparametric item response theory (IRT) estimation methods with the posterior predictive model checking method can obtain significance probabilities of fit statistics in a Bayesian framework by accounting for the uncertainty of the parameter estimation and can indicate the location and magnitude of misfit for an item. The purpose of this study is to check the performance of the Bayesian nonparametric method to assess the IRF fit of parametric IRT models for mixed-format tests and compare it with the existing bootstrapping nonparametric method under various conditions.

How Well Do Simulation Studies Inform Decisions About Multistage Testing?

Most research on multistage testing (MST) uses simulated data. This study adds to the literature by using both operational test data and simulated data to compare two different MST designs with regard to proficiency estimation accuracy and module exposure rates and by investigating whether simulation studies and operational test studies yield similar results. Two MST designs (1-2 and 1-3-4 designs) from one state's sixth-grade summative mathematics assessment across two years were compared in this study.

Adaptive Testing With a Hierarchical Item Response Theory Model.

The hierarchical item response theory (H-IRT) model is very flexible and allows a general factor and subfactors within an overall structure of two or more levels. When an H-IRT model with a large number of dimensions is used for an adaptive test, the computational burden associated with interim scoring and selection of subsequent items is heavy. An alternative approach for any high-dimension adaptive test is to reduce dimensionality for interim scoring and item selection and then revert to full dimensionality for final score reporting, thereby significantly reducing the computational burden.

The association of folate and depression: A meta-analysis.

Background: Previous research suggested that folate levels play an important role in the etiology and course of depression. However, the literature has been inconsistent with regard to differences in folate level between individuals with and without depression. The present meta-analysis synthesized the results of previous studies to examine whether individuals with depression had lower levels of folate than individuals without depression.

The relationship among self-determination, self-concept, and academic achievement for students with learning disabilities.

Research suggests that self-determination skills are positively correlated with factors that have been shown to improve academic achievement, but the direct relationship among self-determination, self-concept, and academic achievement is not fully understood. This study offers an empirical explanation of how self-determination and self-concept affect academic achievement for adolescents with learning disabilities after taking into consideration the covariates of gender, income, and urbanicity. In a nationally representative sample (N = 560), the proposed model closely fit the data, with all proposed path coefficients being statistically significant.