Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…

In this article, we adjust the Kuk randomized response model for collecting information on a sensitive characteristic for increased protection and efficiency by making use of forced "yes" and forced "no" responses. We first describe Kuk's model and then the proposed adjustment to Kuk's model. Next, by means of a simulation…

We aim to examine the international student perceived service quality of Business Schools located in Thailand to link it with their intentions to remain loyal. The survey based approach is adopted to collect data from 300 international students enrolled in various business schools in Thailand. All the dimensions of PAKSERV except Personalization…

The primary objective of this study was to examine the effect of missing data on goodness of fit statistics in confirmatory factor analysis (CFA). For this aim, four missing data handling methods; listwise deletion, full information maximum likelihood, regression imputation and expectation maximization (EM) imputation were examined in terms of…

A major obstacle to developing evidenced-based policy is the difficulty of implementing randomized experiments to answer all causal questions of interest. When using a nonexperimental study, it is critical to assess how much the results could be affected by unmeasured confounding. We present a set of graphical and numeric tools to explore the…

While focus on quality in Danish higher education has been growing in recent years, limited attention has been devoted to developing and thoroughly validating instruments that allow collecting data about university students' perceptions of the teaching-learning environment. Based on data from a large sample of Danish university students, a Danish…

Content is related to other aspects of writing, but exactly how they are related has remained unclear or has not received sufficient critical attention. Consequently, in most writing assessments, content has been treated as just one among several relatively distinct but equal elements. However, in this study, the authors have quantified these…

This study gathered, analyzed, and compared perspectives of students who were honors-eligible but never began the program, students who began in honors and discontinued their enrollment, and those who were persisting in honors. Broadly speaking (and not surprisingly), the responses of students persisting in honors reflected the most positive…

This article urges counseling psychology researchers to recognize and report how missing data are handled, because consumers of research cannot accurately interpret findings without knowing the amount and pattern of missing data or the strategies that were used to handle those data. Patterns of missing data are reviewed, and some of the common…

Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…

Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and…

This NCEE Technical Methods report examines how to address the problem of missing data in the analysis of data in Randomized Controlled Trials (RCTs) of educational interventions, with a particular focus on the common educational situation in which groups of students such as entire classrooms or schools are randomized. Missing outcome data are a…

This article introduces a bootstrap generalization to the Modified Parallel Analysis (MPA) method of test dimensionality assessment using factor analysis. This methodology, based on the use of Marginal Maximum Likelihood nonlinear factor analysis, provides for the calculation of a test statistic based on a parametric bootstrap using the MPA…

A maximum likelihood estimation procedure is developed for the simple and the weighted additive models. The data are assumed to be taken by either one of the following methods: (1) categorical ratings--the subject is asked to rate a set of stimuli with respect to an attribute of the stimuli on rating scales with a relatively few observation…

The utility of the three-form design coupled with maximum likelihood methods for estimation of missing values was evaluated. Simulation studies demonstrate that maximum likelihood estimation and multiple imputation methods produce the most efficient and least biased estimates of variances and covariances for normally distributed and slightly…