Mixed methods research is still an evolving area. However, it has various characteristics like "paradigm pluralism", "focus on research questions than the research design" etc. Mixed methods research is not just one phase of a research but it enters into all stages of research process right from the stage of writing the…

This paper presents a novel design for an upper-level undergraduate statistics course structured around data rather than methods. The course is designed around curated datasets to reflect real-world data science practice and engages students in experiential and peer learning using the data science competition platform Kaggle. Peer learning is…

Research funders and policymakers increasingly focus on societal benefits of their investments in research. Research institutions thus face increasing pressure to demonstrate their societal impact to prove their legitimacy and worth. To this end, research institutions need reliable, quantitative methods to measure societal impact. This article…

Our purpose is to proffer QuantCrit methodological approaches to interrogate notions of statistical practice by convention. We present two approaches to meta-analysis and mean effect size calculations for student achievement. The first approach is the conventional approach which applies between-group differences to calculate effect sizes…

Network meta-analysis is a popular method to synthesize the information obtained in a systematic review of studies (e.g., randomized clinical trials) involving subsets of multiple treatments of interest. The dominant method of analysis employs within-study information on treatment contrasts and integrates this over a network of studies. One…

This paper presents an application of the Kalman filter in signal processing in instrumentation systems when the conditions of the environment generate a large amount of interference for the acquisition of signals from measurement systems. The unwanted interferences make important use of the instrumentation system resources and do not represent…

The COVID-19 Pandemic has presented the educational system with challenges that have caused adaptive instruction techniques for all student populations in one way or another. The researcher chose to focus specifically on the impact of adaptive instruction as a result of the COVID-19 Pandemic in the area of mathematics by evaluating student growth…

With the shift to remote teaching, many instructors used Zoom for synchronous work. However, this presented issues (fatigue, turning cameras off, inequitable technical hurdles) that motivated quantitative reasoning (QR) instructors to look for asynchronous alternatives. A common technique has been textbased online discussions, which can be…

This simulation study examines the characteristics of the Explanatory Item Response Model (EIRM) when estimating treatment effects when compared to classical test theory (CTT) sum and mean scores and item response theory (IRT)-based theta scores. Results show that the EIRM and IRT theta scores provide generally equivalent bias and false positive…

Reliable measurements are key to social science research. Multiple measures of reliability of the total score have been developed, including coefficient alpha, coefficient omega, the greatest lower bound reliability, and others. Among these, the coefficient alpha has been most widely used, and it is reported in nearly every study involving the…

We used simulation techniques to assess the item-level and familywise Type I error control and power of an IRT item-fit statistic, the "S-X"[superscript 2]. Previous research indicated that the "S-X"[superscript 2] has good Type I error control and decent power, but no previous research examined familywise Type I error control.…

Ordinary least squares (OLS) regression and orthogonal regression (OR) address different questions and make different assumptions about errors. The OLS regression of Y on X yields predictions of a dependent variable (Y) contingent on an independent variable (X) and minimizes the sum of squared errors of prediction. It assumes that the independent…

We address measurement error bias in propensity score (PS) analysis due to covariates that are latent variables. In the setting where latent covariate X is measured via multiple error-prone items W, PS analysis using several proxies for X--the W items themselves, a summary score (mean/sum of the items), or the conventional factor score (i.e.,…

In this paper we reflect on the looming question of what constitutes expertise in ethics. Based on an empirical program that involved qualitative and quantitative as well as participatory research elements we show that expertise in research ethics and integrity is based on experience in the assessment processes. We then connect traditional…

Large amounts of missing data could distort item parameter estimation and lead to biased ability estimates in educational assessments. Therefore, missing responses should be handled properly before estimating any parameters. In this study, two Monte Carlo simulation studies were conducted to compare the performance of four methods in handling…