Latent change score (LCS) models are a powerful class of structural equation modeling that allows researchers to work with latent difference scores that minimize measurement error. LCS models define change as a function of prior status, which makes it well-suited for modeling developmental theories or processes. In LCS models, like other latent…

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 dissertation develops and applies sophisticated Item Response Theory (IRT) methods to address fundamental measurement challenges in cognitive testing, focusing on the Armed Services Vocational Aptitude Battery (ASVAB) data from the National Longitudinal Survey of Youth (NLSY). The first chapter implements a confirmatory multidimensional IRT…

In Huggins-Manley & Han (2017), it was shown that WLSMV global model fit indices used in structural equating modeling practice are sensitive to person parameter estimate RMSE and item difficulty parameter estimate RMSE that results from local dependence in 2-PL IRT models, particularly when conditioning on number of test items and sample size.…

This research study examined the specific categories of IT control deficiencies and their related effects on financial reporting. The approach to this study was considered non-experimental, an approach sometimes called descriptive. Descriptive statistics are used to describe the basic features of the data in a study, providing simple summaries…

In the modern world information has become the new power. An increasing amount of efforts are being made to gather data, resources being allocated, time being invested and tools being developed. Data collection is no longer a myth; however, it remains a great challenge to create value out of the enormous data that is being collected. Data modeling…

Many methods exist for imputing missing data but fewer methods have been proposed to test the missing data mechanism. Little (1988) introduced a multivariate chi-square test for the missing completely at random data mechanism (MCAR) that compares observed means for each pattern with expectation-maximization (EM) estimated means. As an alternative,…

Many telephone surveys require interviewers to observe and record respondents' gender based solely on respondents' voice. Researchers may rely on these observations to: (1) screen for study eligibility; (2) determine skip patterns; (3) foster interviewer tailoring strategies; (4) contribute to nonresponse assessment and adjustments; (5)…

This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…

Phonics was identified as one of the critical components in reading development by the National Reading Panel. Over time, research has repeatedly identified phonics as important to early reading development. Given the compelling evidence supporting the teaching of phonics in early reading, it is critical to make sure that instructional decisions…