This Monte Carlo study examined the relative performance of four missing data treatment (MDT) approaches applied to incomplete cross-sectional hierarchical data: maximum likelihood (ML) estimation, multiple imputation under a normal model (MI/NM), multiple imputation under a linear mixed model...

Response time has been regarded as an important source for investigating the relationship between human performance and response speed. It is important to examine the relationship between response time and item characteristics, especially in the perspective of the relationship between response...

For the past forty years, alternative methods and techniques have been researched and developed in light of reducing the burgeoning knowledge and memory requirements of individual workers. One such method is reliance on print-based job aids designed to reduce the amount of complex information...

The purpose of the present study was to investigate empirically the sensitivity of 12 commonly used SEM fit indices derived from ML estimation method to degree and type of model misspecification under different sample size conditions. Moreover, the study evaluated the efficacy of cutoff score...

The purpose of this study was to investigate the performance of the parametric bootstrap method and to compare the parametric and nonparametric bootstrap methods for estimating the standard error of equating (SEE) under the common-item nonequivalent groups (CINEG) design with the frequency...

Broadening the term augmented testing to include a combination of multiple measures to assess examinee performance on a single construct, the issues of IRT item parameter and proficiency estimates were investigated. The intent of this dissertation is to determine if different IRT calibration...

This study investigated the extent to which rules proposed by Tong and Brennan (2007) for estimating standard errors of estimated variance components held up across a variety of G theory designs, variance component structures, sample size patterns, and data types. Simulated data was generated...

This dissertation investigates the interaction of population invariance, equating assumptions, and equating accuracy with group differences. In addition, matched samples equating methods are considered as a possible way to improve equating accuracy with large group differences.Data from one...

The measurement of achievement growth raises many challenges, including how to define "growth" and select or develop a growth measure that captures that definition. Despite these complications, current federal educational policies focus on student growth measures for accountability purposes....

Smoothing techniques are designed to improve the accuracy of equating functions. The main purpose of this dissertation was to propose a new statistic (CS) and compare it to existing model selection strategies in selecting smoothing parameters for polynomial loglinear presmoothing (C) and cubic...