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Almehrizi, Rashid S. – Journal of Educational Measurement, 2021
Estimates of various variance components, universe score variance, measurement error variances, and generalizability coefficients, like all statistics, are subject to sampling variability, particularly in small samples. Such variability is quantified traditionally through estimated standard errors and/or confidence intervals. The paper derived new…
Descriptors: Error of Measurement, Statistics, Design, Generalizability Theory
Nazari, Sanaz; Leite, Walter L.; Huggins-Manley, A. Corinne – Journal of Experimental Education, 2023
The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is…
Descriptors: Growth Models, Statistical Analysis, Intervention, Comparative Analysis
Tsaousis, Ioannis; Sideridis, Georgios D.; AlGhamdi, Hannan M. – Journal of Psychoeducational Assessment, 2021
This study evaluated the psychometric quality of a computerized adaptive testing (CAT) version of the general cognitive ability test (GCAT), using a simulation study protocol put forth by Han, K. T. (2018a). For the needs of the analysis, three different sets of items were generated, providing an item pool of 165 items. Before evaluating the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Cognitive Ability
Tong, Xin; Zhang, Zhiyong – Grantee Submission, 2020
Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…
Descriptors: Robustness (Statistics), Bayesian Statistics, Models, Error of Measurement
Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C. – Educational and Psychological Measurement, 2018
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…
Descriptors: Error of Measurement, Testing, Scores, Models
Lin, Chih-Kai – Language Testing, 2017
Sparse-rated data are common in operational performance-based language tests, as an inevitable result of assigning examinee responses to a fraction of available raters. The current study investigates the precision of two generalizability-theory methods (i.e., the rating method and the subdividing method) specifically designed to accommodate the…
Descriptors: Data Analysis, Language Tests, Generalizability Theory, Accuracy
Kelly, Sean; Ye, Feifei – Journal of Experimental Education, 2017
Educational analysts studying achievement and other educational outcomes frequently encounter an association between initial status and growth, which has important implications for the analysis of covariate effects, including group differences in growth. As explicated by Allison (1990), where only two time points of data are available, identifying…
Descriptors: Regression (Statistics), Models, Error of Measurement, Scores
Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon – Educational and Psychological Measurement, 2014
Previous research has demonstrated that differential item functioning (DIF) methods that do not account for multilevel data structure could result in too frequent rejection of the null hypothesis (i.e., no DIF) when the intraclass correlation coefficient (?) of the studied item was the same as the ? of the total score. The current study extended…
Descriptors: Test Bias, Correlation, Scores, Comparative Analysis
Wilson, Celia M. – ProQuest LLC, 2010
Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…
Descriptors: Monte Carlo Methods, Measurement, Multivariate Analysis, Error of Measurement
Zimmerman, Donald W. – Educational and Psychological Measurement, 2007
Properties of the Spearman correction for attenuation were investigated using Monte Carlo methods, under conditions where correlations between error scores exist as a population parameter and also where correlated errors arise by chance in random sampling. Equations allowing for all possible dependence among true and error scores on two tests at…
Descriptors: Monte Carlo Methods, Correlation, Sampling, Data Analysis
Romano, Jeanine; Kromrey, Jeffrey D. – 2002
The purpose of this study was to examine the potential impact of selected methodological factors on the validity of conclusions from reliability generalization (RG) studies. The study focused on four factors; (1) missing data in the primary studies; (2) transformation of sample reliability estimates; (3) use of sample weights for estimating mean…
Descriptors: Error of Measurement, Monte Carlo Methods, Reliability, Research Methodology

You, Soon-Hyung; Stone-Romero, Eugene F. – Educational and Psychological Measurement, 1996
To clarify the findings of R. Gillett (1991) about the inequality of the means of test scores of minority and majority examinees, the standard errors of the quota-selected sample means and the sampling distribution of these means were studied through Monte Carlo simulation. Results explain that the quota selection inequality results from…
Descriptors: Error of Measurement, Minority Groups, Monte Carlo Methods, Sampling
Kang, Sun-Mee; Waller, Niels G. – Applied Psychological Measurement, 2005
Two Monte Carlo studies were conducted to explore the Type I error rates in moderated multiple regression (MMR) of observed scores and estimated latent trait scores from a two-parameter logistic item response theory (IRT) model. The results of both studies showed that MMR Type I error rates were substantially higher than the nominal alpha levels…
Descriptors: Multiple Regression Analysis, Interaction, Monte Carlo Methods, Item Response Theory
Ziomek, Robert L.; Szymczuk, Mike – 1983
In order to evaluate standard setting procedures, apart from the more commonly applied approach of simply comparing the derived standards or failure rates across various techniques, this study investigated the errors of classification associated with the contrasting groups procedures. Monte Carlo simulations were employed to produce…
Descriptors: Classification, Computer Simulation, Error of Measurement, Evaluation Methods
Smith, Philip L. – 1980
Accurate estimation of variance components used in generalizability theory is essential for the theory to be viewed as an efficacious mechanism for studying the reliability and validity of a measurement procedure. This paper explores two alternatives for dealing with the apparent instability of small sample size used in determining the accuracy of…
Descriptors: Analysis of Variance, Error of Measurement, High Schools, Measurement Techniques
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