The present simulation study examined the statistical properties (namely, Type I error and statistical power) of various novel randomized single-case multiple-baseline designs and associated randomized-test analyses for comparing the A- to B-phase immediate abrupt outcome changes in two independent intervention conditions. It was found that with…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Analyses that reveal how treatment effects vary allow researchers, practitioners, and policymakers to better understand the efficacy of educational interventions. In practice, however, standard statistical methods for addressing heterogeneous treatment effects (HTE) fail to address the HTE that may exist "within" outcome measures. In…

Intervention researchers often use curriculum-based measurement of reading fluency (CBM-R) with a brief experimental analysis (BEA) to identify an effective intervention for individual students. The current study synthesized data from 22 studies that used CBM-R data within a BEA by computing the standard error of measure (SEM) for the median data…

There has been a growing need felt by practitioners, researchers, and evaluators to obtain a common measure of science engagement that can be used in different out-of-school time (OST) science learning settings. We report on the development and validation of a novel 10-item self-report instrument designed to measure, communicate, and ultimately…

Program evaluation often suffers due to time constraints, imperfect instruments, incomplete data, and the need to report standardized metrics. This article about the evaluation process for the Wi$eUp financial education program showcases the difficulties inherent in evaluation and suggests best practices for assessing program effectiveness. We…

We study a popular dual enrollment program in Washington State, "Running Start" using a new administrative database that links high school and postsecondary data. Conditional on prior high school performance, we find that students participating in Running Start are more likely to attend any college but less likely to attend four-year…

We study a popular dual enrollment program in Washington State, "Running Start" using a new administrative database that links high school and postsecondary data. Conditional on prior high school performance, we find that students participating in Running Start are more likely to attend any college but less likely to attend four-year…

In a pretest-posttest cluster-randomized trial, one of the methods commonly used to detect an intervention effect involves controlling pre-test scores and other related covariates while estimating an intervention effect at post-test. In many applications in education, the total post-test and pre-test scores that ignores measurement error in the…

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Equivocal evidence exists regarding the degree of cognitive stability and prevalence of cognitive impairment in very late life. The objective of the current study was to examine mental status performance and change over time within a sample of Iowa centenarians. The baseline sample consisted of 152 community-dwelling and institutionalized…

Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…

To reduce the high incidence of cervical cancer among Latinas in the United States it is important to understand factors that predict screening behavior. The aim of this study was to test the utility of theory of planned behavior in predicting cervical cancer screening among a group of Latinas. A sample of Latinas (N = 614) completed a baseline…

The purpose of this study was to examine the impact of probe variability on the ability to replicate results in brief experimental analysis (BEA) of reading. In the first phase of the study, 41 first- and second- grade students completed 16 oral reading fluency probes. Calculations of probe difficulty were used to identify Low and High Variability…

Multisite trials can clarify the average impact of a new program and the heterogeneity of impacts across sites. Unfortunately, in many applications, compliance with treatment assignment is imperfect. For these applications, we propose an instrumental variable (IV) model with person-specific and site-specific random coefficients. Site-specific IV…