It is meaningful to create a comprehensive score to extract information from mass continuous data when they measure the same latent concept. Therefore, this study adopts the logic of psychometrics to conduct scales on continuous data under the Rasch models. This study also explores the effect of different data discretization methods on scale…

Researchers who use measurement models for evaluation purposes often select models with stringent requirements, such as Rasch models, which are parametric. Mokken Scale Analysis (MSA) offers a theory-driven nonparametric modeling approach that may be more appropriate for some measurement applications. Researchers have discussed using MSA as a…

We propose a new method for analyzing and visualizing information on a large collection of personal networks to uncover the socio-centric structure of relationships among aggregated actors that we clustered into categories. The network of categories identifies the links between groups of sampled ego actors sharing a given attribute (e.g.,…

It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…

This study employs advanced data mining techniques to investigate the DASS-42 questionnaire, a widely used psychological assessment tool. Administered to 680 students at Necmettin Erbakan University's Ahmet Kelesoglu Faculty of Education, the DASS-42 comprises three distinct subscales--depression, anxiety and stress--each consisting of 14 items.…

Quantitative evidence synthesis methods aim to combine data from multiple medical trials to infer relative effects of different interventions. A challenge arises when trials report continuous outcomes on different measurement scales. To include all evidence in one coherent analysis, we require methods to "map" the outcomes onto a single…

Purpose: The analysis of Ecological Momentary Assessment (EMA) data can be difficult to conceptualize due to the complexity of how the data are collected. The goal of this tutorial is to provide an overview of statistical considerations for analyzing observational data arising from EMA studies. Method: EMA data are collected in a variety of ways,…

It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…

Item Response Theory (IRT) models are a popular analytic method for self report data. We show how traditional IRT models can be vulnerable to specific kinds of asymmetric measurement error (AME) in self-report data, because the models spread the error to all estimates -- even those of items that do not contribute error. We quantify the impact of…

This paper seeks to empirically validate a sector agonistic instrument that measures the perceived critical success factors in data governance. Twelve constructs (Leadership and Management Commitment; Leadership and Management Alignment; Executive Sponsorship; Robust Data Governance Strategy; Change Management; Training and Education; Governance…

Purpose: Scholars are increasingly paying attention to the characteristics of effective citizenship education. The systematic use of data to maximise student learning, also called an output-driven approach, is often presented as a powerful predictor of student outcomes. However, its effectiveness has not been studied in citizenship education.…

The first step to addressing equity gaps is to identify them. How can community colleges determine, with some degree of certainty, whether one or more student groups on a campus is in need of assistance in order to succeed? This paper tackles this question by delving into the three methods typically used to identify equity gaps, comparing and…

Manipulation checks are an essential component of quality experimental design in motor learning. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, this methodological systematic review examined the utilization of manipulation checks in focus of attention research. Seventy-eight protocols from four…

Despite the relative youth of bibliometric web platforms (Google Scholar was released in 2004), they play an increasingly significant role in the assessment of the impact of scholars and the research they produce. This scholarly essay provides a thorough review of the literature on bibliometric platforms, the extent to which they make available…

There are a number of ways that student investment can be measured, including full cost of attendance (COA, also known as sticker price), net price (COA minus grant aid), and opportunity costs in the form of forgone earnings. This paper explores those options and makes recommendations for how student investment should be measured with ideal data…