Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…

The recent commentary by Beaujean and Farmer (2020) on the original paper by Dixon et al. (2019) serves a cautionary tale of selective p-values, the law of small N sizes, and the type-II error. We believe these authors have crafted a somewhat questionable argument in which only 57% of the original Dixon et al. data were re-analyzed, based on a…

Purpose: Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation…

Standard meta-analysis methods are vulnerable to bias from incomplete reporting of results (both publication and outcome reporting bias) and poor study quality. Several alternative methods have been proposed as being less vulnerable to such biases. To evaluate these claims independently we simulated study results under a broad range of conditions…

In Bayesian statistics, the most widely used criteria of Bayesian model assessment and comparison are Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). A multilevel mediation model is used as an illustrative example to compare different types of DIC and WAIC. More specifically, the study compares the…

Doubly robust (DR) estimators that combine regression adjustments and inverse probability weighting (IPW) are widely used in causal inference with observational data because they are claimed to be consistent when either the outcome or the treatment selection model is correctly specified (Scharfstein et al., 1999). This property of "double…

The standard regression technique for modeling binary response variables in education research is logistic regression. The odds ratios from these models are used to quantify and communicate variable effects. These effects are sometimes pooled together as in a meta-analysis. We argue that this process is problematic as odds ratios calculated from…

Although the null hypothesis significance testing procedure is problematic, many still favor the use of "p"-values as indicating the state of evidence against the model used to generate the "p"-value. From this perspective, "p"-values benefit science; or would benefit science if used correctly. In contrast, the novel…

The purpose of this study was to compare and contrast frameworks for evaluating methodological rigor in single case research. Specifically, research on high-probability requests to increase compliance in young children was evaluated. Ten studies were identified and were coded using 4 frameworks. These frameworks were the Council for Exceptional…

This report aims to showcase the value of implementing a Bayesian framework to analyse and report results from international large-scale surveys and provide guidance to users who want to analyse the data using this approach. The motivation for this report stems from the recognition that Bayesian statistical inference is fast becoming a popular…

Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often. While smartphones are commonly used in some groups of individuals, smartphone penetration is significantly lower in other groups. In addition, different operating systems (OSs) limit how mobile data…

When a psychologist announces a new research finding, it is often based on a rejected null hypothesis. However, if that hypothesis is true, the claim is a false alarm. Many students mistakenly believe that the probability of committing a false alarm equals alpha, the criterion for statistical significance, which is typically set at 5%. Instructors…

Case-mix heterogeneity across studies complicates meta-analyses. As a result of this, treatments that are equally effective on patient subgroups may appear to have different effectiveness on patient populations with different case mix. It is therefore important that meta-analyses be explicit for what patient population they describe the treatment…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

In this paper, we investigate two purported problems with Bayesian Knowledge Tracing (BKT), a popular statistical model of student learning: "identifiability" and "semantic model degeneracy." In 2007, Beck and Chang stated that BKT is susceptible to an "identifiability problem"--various models with different…