In science in general and in the context of single-case experimental designs, replication of the effects of the intervention within and/or across participants or experiments is crucial for establishing causality and for assessing the generality of the intervention effect. Specific developments and proposals for assessing whether an effect has been…

Conventional advice discourages controlling for postoutcome variables in regression analysis. By contrast, we show that controlling for commonly available postoutcome (i.e., future) values of the treatment variable can help detect, reduce, and even remove omitted variable bias (unobserved confounding). The premise is that the same unobserved…

In educational contexts, students often self-select into specific interventions (e.g., courses, majors, extracurricular programming). When students self-select into an intervention, systematic group differences may impact the validity of inferences made regarding the effect of the intervention. Propensity score methods are commonly used to reduce…

Education decisionmakers need access to the best evidence about the effectiveness of education interventions, including practices, products, programs, and policies. It can be difficult, time consuming, and costly to access and draw conclusions from relevant studies about the effectiveness of interventions. The What Works Clearinghouse (WWC)…

Latent variable structural equation modeling has become the analytic method of choice in many domains of research in psychology and allied social sciences. One important aspect of a latent variable model concerns the relations hypothesized to hold between latent variables and their indicators. The most common specification of structural equation…

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

This article offers reflections on the development of the Rubin causal model (RCM), which were stimulated by the impressive discussions of the RCM and Campbell's superb contributions to the practical problems of drawing causal inferences written by Will Shadish (2010) and Steve West and Felix Thoemmes (2010). It is not a rejoinder in any real…

Education policy-makers and practitioners want to know which policies and practices can best achieve their goals. But research that can inform evidence-based policy often requires complex methods to distinguish causation from accidental association. Avoiding econometric jargon and technical detail, this paper explains the main idea and intuition…

Some form of a short interrupted time series (ITS) is often used to evaluate state and national programs. An ITS design with a single treatment group assumes that the pretest functional form can be validly estimated and extrapolated into the postintervention period where it provides a valid counterfactual. This assumption is problematic. Ambiguous…

In this article, we note the many ontological, epistemological, and methodological similarities between how Campbell and Rubin conceptualize causation. We then explore 3 differences in their written emphases about individual case matching in observational studies. We contend that (a) Campbell places greater emphasis than Rubin on the special role…

Matching methods such as nearest neighbor propensity score matching are increasingly popular techniques for controlling confounding in nonexperimental studies. However, simple k:1 matching methods, which select k well-matched comparison individuals for each treated individual, are sometimes criticized for being overly restrictive and discarding…

This review focuses on what the author terms a reconsideration of the working credentials of the randomly controlled trial (RCT) design, and includes a discussion of popularly accepted aspects as well as some new perspectives. The author concludes that there is nothing either Imperative or superior about the need for RCT designs, and that an…

This article highlights the problem of omitted variable bias in research on the causal effect of financial aid on college-going. I first describe the problem of self-selection and the resulting bias from omitted variables. I then assess and explore the strengths and weaknesses of random assignment, multivariate regression, proxy variables, fixed…

A rich narrative-style bibliography of concept mapping (reviewing six articles published between 1992-2005). Articles reviewed include: (1) Cognitive mapping: A qualitative research method for social work (C. Bitoni); (2) Collaborative concept mapping: Provoking and supporting meaningful discourse (C. Boxtel, J. Linden, E. Roelofs, and G. Erkens);…

Counterfactuals are routinely used in physical and biological sciences to develop and evaluate sophisticated, non-linear models. They have been used with telling effect in the study of economic history and American politics. For some historians, counterfactual arguments have no scholarly standing. They consider them flights of fancy, fun over a…