This paper studies the effect of the Head Start program on children's achievements in reading and math tests during their first 4 years of schooling after completing the program. Using nationally representative data from the Early Childhood Longitudinal Study, I found large measurement error in the parental reports of Head Start attendance, which…

In 2002, an article entitled "Four assumptions of multiple regression that researchers should always test" by Osborne and Waters was published in "PARE." This article has gone on to be viewed more than 275,000 times (as of August 2013), and it is one of the first results displayed in a Google search for "regression…

This study examined the applicability of the Arabic version of the Curriculum Based Measurement Maze (CBM Maze) for Jordanian students. A sample of 150 students was recruited from two public primary schools in Jordan. The students were ranked into high, moderate, and low achievers in terms of their performance in the Arabic course. Then all of…

In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data…

There are relatively few examples of quantitative approaches to quality control in educational assessment and accountability contexts. Among the several techniques that are used in other fields, Shewart charts have been found in a few instances to be applicable in educational settings. This paper describes Shewart charts and gives examples of how…

Interaction and quadratic effects in latent variable models have to date only rarely been tested in practice. Traditional product indicator approaches need to create product indicators (e.g., x[superscript 2] [subscript 1], x[subscript 1]x[subscript 4]) to serve as indicators of each nonlinear latent construct. These approaches require the use of…

Interest in testing interaction terms within the latent variable modeling framework has been on the rise in recent years. However, little is known about the influence of nonnormality and model misspecification on such models that involve latent variable interactions. The authors used Mattson's data generation method to control for latent variable…

Nonparametric or kernel regression estimation of item response curves (IRCs) is often used in item analysis in testing programs. These estimates are biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. Accuracy of this estimation is a concern theoretically and operationally.…

A marginal maximum a posteriori (MMAP) procedure was implemented to estimate item parameters in the generalized graded unfolding model (GGUM). Estimates from the MMAP method were compared with those derived from marginal maximum likelihood (MML) and Markov chain Monte Carlo (MCMC) procedures in a recovery simulation that varied sample size,…

This manual provides guidance and documentation for users of the longitudinal kindergarten-fourth grade (K-4) data file of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). It mainly provides information specific to the fourth-grade round of data collection. The first chapter provides an overview of the…

We develop a Bayesian hierarchical model for the analysis of ordinal data from multirater ranking studies. The model for a rater's score includes four latent factors: one is a latent item trait determining the true order of items and the other three are the rater's performance characteristics, including bias, discrimination, and measurement error…

Growth mixture modeling (GMM) is a relatively new technique for analyzing longitudinal data. However, when applying GMM, researchers might assume that the higher level (nonrepeated measure) units (e.g., students) are independent from each other even though it might not always be true. This article reports the results of a simulation study…

In this paper we propose an upward correction to the standard error (SE) estimation of theta[subscript ML], the maximum likelihood (ML) estimate of the latent trait in item response theory (IRT). More specifically, the upward correction is provided for the SE of theta[subscript ML] when item parameter estimates obtained from an independent pretest…

The Total Survey Error (TSE) paradigm provides a framework that supports the effective planning of research, guides decision making about data collection and contextualises the interpretation and dissemination of findings. TSE also allows researchers to systematically evaluate and improve the design and execution of ongoing survey programs and…

Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…