Sensitivity analyses can inform evidence-based education policy by quantifying the hypothetical conditions necessary to change an inference. Perhaps the most prevalent index used for sensitivity analyses is Oster's (2019) Coefficient of Proportionality (COP). Oster's COP leverages changes in estimated effects and R[superscript 2] when observed…

This study incorporates a random forest (RF) approach to probe complex interactions and nonlinearity among predictors into an item response model with the goal of using a hybrid approach to outperform either an RF or explanatory item response model (EIRM) only in explaining item responses. In the specified model, called EIRM-RF, predicted values…

Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently,…

Despite the broad appeal of missing data handling approaches that assume a missing at random (MAR) mechanism (e.g., multiple imputation and maximum likelihood estimation), some very common analysis models in the behavioral science literature are known to cause bias-inducing problems for these approaches. Regression models with incomplete…

We consider two-level models where a continuous response R and continuous covariates C are assumed missing at random. Inferences based on maximum likelihood or Bayes are routinely made by estimating their joint normal distribution from observed data R[subscript obs] and C[subscript obs]. However, if the model for R given C includes random…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Latent change score models (LCS) are conceptually powerful tools for analyzing longitudinal data (McArdle & Hamagami, 2001). However, applications of these models typically include constraints on key parameters over time. Although practically useful, strict invariance over time in these parameters is unlikely in real data. This study…

In the analysis of causal effects in non-experimental studies, conditioning on observable covariates is one way to try to reduce unobserved confounder bias. However, a developing literature has shown that conditioning on certain covariates may increase bias, and the mechanisms underlying this phenomenon have not been fully explored. We add to the…

Using nationally representative data from the Family and Child Experiences Survey 2009 Cohort (n = 2,798), this study examined patterns of absenteeism and their consequences through the transition to kindergarten. Overall, children were less likely to be absent in kindergarten than from Head Start at ages 3 and 4. Absenteeism was fairly stable…

Self-explanations are commonly used to assess on-line reading comprehension processes. However, traditional methods of analysis ignore important temporal variations in these explanations. This study investigated how dynamical systems theory could be used to reveal linguistic patterns that are predictive of self-explanation quality. High school…

We examined individual differences and predictions of children's patterns in behavioral, emotional and attentional efforts toward challenging puzzle tasks at 24 and 35 months using data from a large longitudinal rural representative sample. Using latent transition analysis, we found four distinct task-oriented patterns in problem-solving tasks…

Because math knowledge begins to develop at a young age to varying degrees, it is important to identify foundational cognitive and academic skills that might contribute to its development. The current study focused on two important, but often overlooked skills that recent evidence suggests are important contributors to early math development:…

This study explored the background knowledge (BK) and reading comprehension (RC) relationship for struggling adult readers. Using confirmatory factor analyses, a single-factor BK model exhibited better fit than a two-factor model separating academic knowledge and general information, which indicates that BK represents a unidimensional construct…

Accumulating research has established explicit mathematics instruction as an evidence-based teaching practice. This study utilized observation data from a multi-year efficacy trial to examine the longitudinal effect of a core kindergarten mathematics program on the use of explicit mathematics instruction among two distinct groups of teachers: one…

An important topic in writing research has been the use of cohesive features. Much of this research has focused on local and text cohesion. The few studies that have studied global cohesion have been restricted to first language writing. This study investigates the development of local, global, and text cohesion in the writing of 57 language (L2)…