Determining the number of dimensions underlying many variables in the data or many items in the test is a crucial process prior to performing exploratory factor analysis. Failure to do so leads to serious consequences concerning construct validity. Parallel analysis (PA) has been found to be useful to determine the number of dimensions (i.e.,…

The Federal Employee Viewpoint Survey is an annual survey of over 800,000 permanently employed civilian personnel from 87 agencies. First administered in 2002, the web-based survey measures a broad range of employee perceptions, attitudes, and behaviors, serving as a valuable tool for human resources managers to determine which aspects of an…

Taking more than one measurement of the same variable also hosts the possibility of contamination from error sources, both singly and in combination as a result of interactions. Therefore, although the internal consistency of scores received from measurement tools is examined by itself, it is necessary to ensure interrater or intra-rater agreement…

Investigation of measurement invariance (MI) commonly assumes correct specification of dimensionality across multiple groups. Although research shows that violation of the dimensionality assumption can cause bias in model parameter estimation for single-group analyses, little research on this issue has been conducted for multiple-group analyses.…

This publication describes the methods and procedures used for the 2017-18 National Postsecondary Student Aid Study, Administrative Collection (NPSAS:18-AC). It also provides information that will be helpful to analysts in accessing and understanding the restricted-use files containing the NPSAS:18-AC data. NPSAS:18-AC includes cross-sectional,…

In the current day and age, innovation is the fodder that keeps companies and institutions running, and universities play an important role. During the crisis and in the post-crisis period, financial support for research and development have undergone significant changes especially at universities. The aim of this research is to conduct a patent…

This research note discusses opportunities and challenges of using online survey engines for social network analysis (SNA) data collection and assessing sample size and representativeness. The discussion is based on a case study of SNA data collection for a pilot research on health-relevant policy networks in Canada. Our approach demonstrates how…

The present study examines bias in parameter estimates and standard error in cross-classified random effect modeling (CCREM) caused by omitting the random interaction effects of the cross-classified factors, focusing on the effect of a sample size within cells and ratio of a small cell. A Monte Carlo simulation study was conducted to compare the…

Recently, interest in test subscore reporting for diagnosis purposes has been growing rapidly. The two simulation studies here examined factors (sample size, number of subscales, correlation between subscales, and three factors affecting subscore reliability: number of items per subscale, item parameter distribution, and data generating model)…

Linking score scales across different tests is considered speculative and fraught, even at the aggregate level (Feuer et al., 1999; Thissen, 2007). We introduce and illustrate validation methods for aggregate linkages, using the challenge of linking U.S. school district average test scores across states as a motivating example. We show that…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

This paper presents the results of an attempt to analyze the benefits and risks of information and communication technologies (ICTs) and their applications, as perceived by university students. A survey was conducted using questionnaire with a free descriptive answering format. Responses were analyzed via text mining and correspondence analysis;…

Multivariate analysis of variance (MANOVA) is a statistical method used to examine group differences on multiple outcomes. This article reports results of a review of MANOVA in gifted education journals between 2011 and 2017 (N = 56). Findings suggest a number of conceptual and procedural misunderstandings about the nature of MANOVA and its…

Measurement invariance is crucial for an effective and valid measure of a construct. Invariance holds when the latent trait varies consistently across subgroups; in other words, the mean differences among subgroups are only due to true latent ability differences. Differential item functioning (DIF) occurs when measurement invariance is violated.…