Background: Educational programs often use student test scores to determine access to some treatment, such as remedial support or graduation (Jacob & Lefgren, 2004; Martorell, 2004; Matsudaira, 2008; Papay et al., 2011, 2014). In these cases, treatment assignment is based on the student's score from one or more subjects. For example, students…

Including a large number of predictors in the imputation model underlying a multiple imputation (MI) procedure is one of the most challenging tasks imputers face. A variety of high-dimensional MI techniques can help, but there has been limited research on their relative performance. In this study, we investigated a wide range of extant…

Mediation analysis in Single Case Experimental Designs (SCEDs) evaluates intervention mechanisms for individuals. Despite recent methodological developments, no clear guidelines exist for maximizing power to detect the indirect effect in SCEDs. This study compares frequentist and Bayesian methods, determining (1) minimum required sample size to…

We study the external validity of instrumental variable estimation. The key assumption we impose for external validity is conditional external unconfoundedness among compliers, which means that the treatment effect and target selection are independent among compliers conditional on covariates. We study this assumption with a case study about the…

The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…

Despite the availability and potential usefulness of demographic and contextual data in many quantitative studies within engineering education, the preference for ANOVA over regression models remains prevalent, often without clear justification. A mapping review of literature from the EJEE and JEE spanning 2012-2022 identified 98 studies using…

Common sense is a dynamic concept and it is natural that our (statistical) common sense lags behind the development of statistical science. What is not so easy to understand is why common sense lags behind as much as it does. We conduct a survey among Japanese students and provide examples and tentative explanations of a number of statistical…

Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…

Matching methods are widely used in educational research to estimate causal effects when randomization is not feasible. These techniques pair treated units (such as schools receiving an intervention) with similar control units based on observable characteristics. However, current statistical inference procedures for these methods can produce…

The difference in differences design is widely used to assess treatment effects in natural experiments or other situations where random assignment cannot, or is not, used (see, e.g., Angrist & Pischke, 2009). The researcher must make important decisions about which comparisons to make, the measurements to make, and perhaps the number of…

Current research on intergenerational mobility (IGM) is informed by "statistical" approaches based on log-level regressions, whose "economic" interpretations remain largely unknown. We reveal the subjective value-judgments in them: they are represented by weighted-sums (or aggregators) over heterogeneous groups, with…

Background: Double/debiased machine learning (DML) methods have been proposed to overcome the regularization bias from the naive approach of ML methods (Chernozhukov et al., 2018). DML methods use a partialling-out approach which removes the effect of confounders from both the treatment and outcome and then regresses the residualized outcome on…

Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently,…

School start regulations allocate children born immediately either side of a given date to different life paths: those slightly older starting school a full year earlier. School effectiveness literature exploits this to estimate causal effects described as 'the absolute effect of schooling' or 'the effect of an additional year's schooling', using…

We consider the cascading effects of researcher decisions throughout the process of quantifying racially polarized voting (RPV). We contrast three methods of estimating precinct racial composition, Bayesian Improved Surname Geocoding (BISG), fully Bayesian BISG, and Citizen Voting Age Population (CVAP), and two algorithms for performing ecological…