Causal asymmetry is a situation where the causal factors under study are more suitable for explaining the outcome than its absence (or vice versa); they do not explain both equally well. In such a situation, presence of a cause leads to presence of the effect, but absence of the cause may not lead to absence of the effect. A conceptual discussion…

Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…

In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…

Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal effect is defined as a comparison of the potential outcomes of the same units under different treatment conditions. Because for each unit at most one of the potential…

As the socio-linguistic make-up of the United States shifts from an English monolingual country to a multilingual society, it becomes imperative that a pool of linguistically, knowledgeable, competent nurses are in the pipeline to the nursing workforce to meet the needs of a diverse lingual patient population. The continued lack of…

Regression discontinuity design (RD) has been widely used to produce reliable causal estimates. Researchers have validated the accuracy of RD design using within study comparisons (Cook, Shadish & Wong, 2008; Cook & Steiner, 2010; Shadish et al, 2011). Within study comparisons examines the validity of a quasi-experiment by comparing its…

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.…

The authors propose and test a causal model theory of reasoning about conditional arguments with causal content. According to the theory, the acceptability of modus ponens (MP) and affirming the consequent (AC) reflect the conditional likelihood of causes and effects based on a probabilistic causal model of the scenario being judged. Acceptability…

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…

We contribute to debate about causal inferences in educational research in two ways. First, we quantify how much bias there must be in an estimate to invalidate an inference. Second, we utilize Rubin's causal model to interpret the bias necessary to invalidate an inference in terms of sample replacement. We apply our analysis to an inference…

This quantitative causal-comparative study compared perceptions of professional development opportunities between high-achieving and low-achieving elementary-middle school teachers in an urban school district using the Standards Assessment Inventory (SAI). A total of 271 teachers participated including 134 (n = 134) teachers from high-achieving…

The sharp regression discontinuity design (RDD) has three key weaknesses compared to the randomized clinical trial (RCT). It has lower statistical power, it is more dependent on statistical modeling assumptions, and its treatment effect estimates are limited to the narrow subpopulation of cases immediately around the cutoff, which is rarely of…

To assess the value of individual students' subscores on the Major Field Test in Business (MFT Business), I examined the test's internal structure with factor analysis and structural equation model methods, and analyzed the subscore reliabilities using the augmented scores method. Analyses of the internal structure suggested that the MFT Business…

Educators continue to have difficulty reforming English curricula in ways that better serve the needs of second language learners. This difficulty is perpetuated, in part, by the inability to predict how such changes will affect morphosyntactic development. To date, ESL research has failed to effectively ascertain how multiple causes influence the…

The number of English language learners (ELLs) within the school system in one Western U.S. state continues to rise; writing scores of ELLs lag well behind those of their English speaking peers. The purpose of this ex post facto quantitative causal comparative study was to examine the writing achievement of fourth grade ELLs instructed within a…