Missing data is a common challenge to any researcher in almost any field of research. In particular, human participants in research do not always respond or return for assessments leaving the researcher to rely on missing data methods. The most common methods (i.e., Multiple Imputation and Full Information Maximum Likelihood) assume that the…

The last two decades have seen a dramatic increase in randomized controlled trials (RCTs) conducted in community colleges. Yet, there is limited empirical information on the design parameters necessary to plan the sample size for RCTs in this context. We provide empirical estimates of key design parameters, discussing lessons based on the pattern…

Practitioners of adult education have a long history of teaching for social change. They may, however, be uncomfortable using quantitative methods to assess the impact of their learning activities, or they might lack access to statistical analysis software. Quantitative methods help the practitioner determine whether behavioral or attitudinal…

Brazil's education system lags behind international standards, with two-fifths of students scoring below the minimum level of proficiency in mathematics, science, and reading. Thus, this study combined machine learning with traditional statistics to identify the most important predictors and to interpret their effects on proficiency in the PISA…

Purpose: Learning organization (LO) concept has received much attention in the last decades. The purpose of an LO is to proactively shape its future by fostering a culture of continuous learning among its members. This approach empowers the organization to adapt, evolve and innovate, aligning with the needs and aspirations of both internal and…

Measurement of latent constructs is one of the most challenging tasks in psychological research. Unlike physical variables, latent constructs are not directly observable but are inferred through individuals' responses to a set of items often referred to as measurement instruments, tests, surveys, or assessments. For decades, exploratory factor…

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…

Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…

The study of transfer in Canadian post-secondary education is a fractured terrain, with vast inter-provincial differences and deep schisms between participating communities. At the time of writing, there exists no comprehensive review that maps the predictors and associated outcomes of transfer in Canada, thus complicating the advancement of this…

Background: Individual patient data meta-analyses (IPD-MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD-MA have been published in recent years, but there is much variation in how these IPD-MA were…

In cognitive diagnostic assessment, multiple fine-grained attributes are measured simultaneously. Attribute hierarchies are considered important structural features of cognitive diagnostic models (CDMs) that provide useful information about the nature of attributes. Templin and Bradshaw first introduced a hierarchical diagnostic classification…

The causal mediation literature has developed techniques to assess the sensitivity of an inference to pretreatment confounding, but these techniques are limited to the case of a single mediator. In this article, we extend sensitivity analysis to possible violations of pretreatment confounding in the case of multiple mediators. In particular, we…

Standard meta-analysis methods are vulnerable to bias from incomplete reporting of results (both publication and outcome reporting bias) and poor study quality. Several alternative methods have been proposed as being less vulnerable to such biases. To evaluate these claims independently we simulated study results under a broad range of conditions…

Nonlinear mixed-effects models are models in which one or more coefficients of the growth model enter in a nonlinear manner, such as appearing in the exponent of the growth function. In their applications, the within-individual residuals are often assumed to be independent with constant variance across time, an assumption that implies that the…

When individuals engage in divergent thinking, they vary on their Elaboration, or the degree to which they explain and embellish their responses. Although Elaboration has been considered relevant to creativity research for decades, its measurement has remained under-developed. Here, we leverage technical and methodological perspectives from the…