This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group…

In many psychological and educational applications, it is imperative to obtain valid and reliable score estimates of multilevel processes. For example, in order to assess the quality and characteristics of high impact learning processes, one must compute accurate scores representative of student- and classroom-level constructs. Currently, there…

Measurement of latent constructs is one of the most challenging tasks in psychological research. Unlike physical variables, latent constructs are not directly observable but are inferred through individuals' responses to a set of items often referred to as measurement instruments, tests, surveys, or assessments. For decades, exploratory factor…

Observable data in empirical social and behavioral science studies are often categorical (i.e., binary, ordinal, or nominal). When categorical data are outcomes, they fail to maintain the scale and distributional properties of linear regression and factor analysis. Attempting to estimate model parameters for categorical outcome data with the…

Higher education institutions face heightened accountability for student success. As such, higher education relies heavily on big data to predict student outcomes. This process is problematic because predictive models are developed on historical data, are deficit based, and are focused on student factors, neglecting institutional factors. The…

This multiple-manuscript dissertation explored the measurement invariance (MI) testing with multiple-group confirmatory factor analysis (MG-CFA) approach from different perspectives. Study 1 explored MI from a theoretical perspective by conducting a systematic review study on MI practices in education. The findings of this study indicated…

Much of the research on the faculty experience has focused on productivity, engagement, satisfaction, and well-being; however, no instrument or theoretical framework that contributes to an understanding of a faculty member's optimal psychological functioning--or thriving--currently exists. The purpose of this study was to address this gap in the…

Seligman (2011) introduced well-being theory as a multidimensional model to increase and measure well-being. The PERMA model of well-being theory defines well-being in terms of five constructs: Positive Emotion, Engagement, Relationships, Meaning, and Accomplishment. Together, these five constructs are the foundation of individual and community…

Recent research in multidimensional item response theory has introduced within-item interaction effects between latent dimensions in the prediction of item responses. The objective of this study was to extend this research to bifactor models to include an interaction effect between the general and specific latent variables measured by an item.…

This dissertation analyzes the production and perception of lexical stress in trilinguals' first, second, and third languages (L1, L2, and L3) to evaluate how the cue-weighting transfer hypothesis applies to L3 acquisition. According to this hypothesis, acoustic cues to stress have different weights across languages, and results from both…

Enabling learners to successfully use their second language (L2) in meaningful ways is a critical goal of instruction. Ultimately, most learners want to meet the L2 demands of the contexts in which they will use the language. To accomplish this, learners must develop linguistic knowledge and apply it in a manner that is contextually appropriate…

Writing support for graduate students is one of the top concerns in the field of graduate writing education and research. The need of graduate writing support through communal writing practice opportunities has not been explored empirically yet. The main purpose of the study is to explore graduate student perception to develop and test a graduate…

Principal component analysis is an important statistical technique for dimension reduction and exploratory data analysis. However, it is not robust to outliers and may obfuscate important data structure such as clustering. We propose a version of principal component analysis based on the robust L2E method. The technique seeks to find the principal…

This dissertation explored whether unnecessary linguistic complexity (LC) in mathematics and biology assessment items changes the direction and significance of differential item functioning (DIF) between subgroups emergent bilinguals (EBs) and English proficient students (EPs). Due to inconsistencies in measuring LC in items, Study One adapted a…

When researchers fit statistical models to multiply imputed datasets, they have to fit the model separately for each imputed dataset. Since there are multiple datasets, there are always multiple sets of model results. It is possible for some of these sets of results not to converge while some do converge. This study examined occurrence of such a…