Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…

This article provides a meta-analysis of studies using the crosswise model (CM) in estimating the prevalence of sensitive characteristics in different samples and populations. On a data set of 141 items published in 33 either articles or books, we compare the difference ([delta]) between estimates based on the CM and a direct question (DQ). The…

The purpose of this research was to compare the performances of the Fixed Effect Model (FEM) and the Random Effects Model (REM) in the meta-analysis studies conducted through 5, 10, 20 and 40 studies with an outlier and 4, 9, 19 and 39 studies without an outlier in terms of estimated common effect size, confidence interval coverage rate and…

A compelling demonstration of implicit learning is the human ability to unconsciously detect and internalize statistical patterns of complex environmental input. This ability, called statistical learning, has been investigated in people with dyslexia using various tasks in different orthographies. However, conclusions regarding impaired or intact…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

Pandemic-related policies are typically developed by districts and translated to all schools for implementation. Understanding the degree to which the pandemic impacted school-level performance would provide additional perspective for researchers looking to help district and school officials move forward. The main purpose of this study is to…

In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In…

This commentary begins by summarizing the five contributions to this special issue and briefly recapping the background to the topic of student learning in higher education. Narrative and systematic reviews are compared, and the relative value of different bibliographic databases in the context of systematic reviews is assessed. The importance of…

A common hypothesis is that students will more deeply understand dynamic systems and other complex phenomena if they construct computational models of them. Attempts to demonstrate the advantages of model construction have been stymied by the long time required for students to acquire skill in model construction. In order to make model…

An odds ratio approach (ORA) under the framework of a nested logit model was proposed for evaluating differential distractor functioning (DDF) in multiple-choice items and was compared with an existing ORA developed under the nominal response model. The performances of the two ORAs for detecting DDF were investigated through an extensive…

This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…

The aim of this study is to compare the 5E learning model with traditional learning methods in terms of their effect on students' academic achievement, retention and attitude scores. In this context, the meta-analytic method known as the "analysis of analyses" was used and a review undertaken of the studies and theses (N = 14) executed…

Background: Large-scale cross-national studies designed to measure student achievement use different social, cultural, economic and other background variables to explain observed differences in that achievement. Prior to their inclusion into a prediction model, these variables are commonly scaled into latent background indices. To allow…

Sloutsky and Fisher (2012) attempt to reframe the results presented in Noles and Gelman (2012) as a pure replication of their original work validating the similarity, induction, naming, and categorization (SINC) model. However, their critique fails to engage with the central findings reported in Noles and Gelman, and their reanalysis fails to…

We meta-analyze for impact and cost-effectiveness 94 studies from 47 conditional cash transfer programs in low- and middle-income countries worldwide, focusing on educational outcomes that include enrollment, attendance, dropout, and school completion. To conceptually guide and interpret the empirical findings of our meta-analysis, we present a…