A research question that is of interest across many disciplines is whether and how relationships in a network are related to the attributes of the nodes of the network. In this dissertation, we propose two joint frameworks for modeling the relationship between the network and attributes. In the joint latent space model in Chapter 2, shared latent…

Economic efficiency demands accurate assessment of individual ability for selection purposes. This study investigates Classical Test Theory (CTT) and Item Response Theory (IRT) for estimating true ability and ranking individuals. Two Monte Carlo simulations and real data analyses were conducted. Results suggest a slight advantage for IRT, but…

This study investigates polytomous item explanatory item response theory models under the multivariate generalized linear mixed modeling framework, using the linear logistic test model approach. Building on the original ideas of the many-facet Rasch model and the linear partial credit model, a polytomous Rasch model is extended to the item…

The frequent practice of overall fit evaluation for latent variable models in educational and behavioral research is reconsidered. It is argued that since overall plausibility does not imply local plausibility and is only necessary for the latter, local misfit should be considered a sufficient condition for model rejection, even in the case of…

In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…

The four-parameter logistic (4PL) Item Response Theory (IRT) model has recently been reconsidered in the literature due to the advances in the statistical modeling software and the recent developments in the estimation of the 4PL IRT model parameters. The current simulation study evaluated the performance of expectation-maximization (EM),…

S-X[superscript 2] is a popular item fit index that is available in commercial software packages such as "flex"MIRT. However, no research has systematically examined the performance of S-X[superscript 2] for detecting item misfit within the context of the multidimensional graded response model (MGRM). The primary goal of this study was…

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…

Mixture IRT models address the heterogeneity in a population by extracting latent classes and allowing item parameters to vary between latent classes. Once the latent classes are extracted, they need to be further examined to be characterized. Some approaches have been adopted in the literature for this purpose. These approaches examine either the…

In this article, the authors extend the results of Aguirre-Urreta, Rönkkö, and Marakas (2016) concerning the omission of a relevant causal indicator by testing the validity of the assumption that causal indicators are entirely superfluous to the measurement model and discuss the implications for measurement theory. Contrary to common wisdom…

Multidimensional Item Response Theory (MIRT) is widely used in assessment and evaluation of educational and psychological tests. It models the individual response patterns by specifying functional relationship between individuals' multiple latent traits and their responses to test items. One major challenge in parameter estimation in MIRT is that…

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…

Student modeling is useful in educational research and technology development due to a capability to estimate latent student attributes. Widely used approaches, such as the Additive Factors Model (AFM), have shown satisfactory results, but they can only handle binary outcomes, which may yield potential information loss. In this work, we propose a…

Mplus is a powerful latent variable modeling software program that has become an increasingly popular choice for fitting complex item response theory models. In this short note, we demonstrate that the two-parameter logistic testlet model can be estimated as a constrained bifactor model in Mplus with three estimators encompassing limited- and…

Lagrange multiplier (LM) or score tests have seen renewed interest for the purpose of diagnosing misspecification in item response theory (IRT) models. LM tests can also be used to test whether parameters differ from a fixed value. We argue that the utility of LM tests depends on both the method used to compute the test and the degree of…