Background: Education researchers typically estimate average program effects with regression; if they are interested in heterogeneous effects, they include an interaction in the model. Such models quantify and infer the influences of each covariate on the effect via interaction coefficients and their associated p-values or confidence intervals.…

In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…

This article reviews important statistical methods for estimating the impact of interventions on outcomes in education settings, particularly programs that are implemented in field, rather than laboratory, settings. We begin by describing the causal inference challenge for evaluating program effects. Then four research designs are discussed that…

This report from the Career and Technical Education (CTE) Research Network Lead team provides final results from an evaluability assessment of CTE programs that feasibly could be evaluated using a rigorous experimental design. Evaluability assessments (also called feasibility studies) are used in education and other fields, such as international…

A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…

Due to an increasing interest in the use of single-subject experimental designs (SSEDs), appropriate techniques are needed to analyze this type of data. The purpose of this paper proposal is to present four studies (Beretvas, Hembry, Van den Noortgate, & Ferron, 2013; Bunuan, Hembry & Beretvas, 2013; Moeyaert, Ugille, Ferron, Beretvas,…

Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…

A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect…

It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…

A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…

This paper illustrates how information collected through interviews can develop a richer understanding of the assignment mechanism, which can result in more plausible causal effect estimates from observational studies and provides a roadmap for sensitivity analysis. Focusing on the issue of assignment to algebra in 8th grade, the author shows how…

A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

Presents an opinion on the appropriate use of significance tests, especially in the context of regression analysis, the most commonly encountered statistical technique in education and related disciplines. Briefly discusses the appropriate use of power analysis. Contains 47 references. (Author/SV)

Contrasts aptitude by treatment interaction (ATI) and hierarchical linear modeling (HLM) methods for making cross-level inferences between individual-level and group-level factors in school effectiveness research. Recommends HLM when intraclass correlations are high. ATI is suitable when intraclass correlations are low, but partitioning the…