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Waterbury, Glenn Thomas; DeMars, Christine E. – Journal of Experimental Education, 2019
There is a need for effect sizes that are readily interpretable by a broad audience. One index that might fill this need is [pi], which represents the proportion of scores in one group that exceed the mean of another group. The robustness of estimates of [pi] to violations of normality had not been explored. Using simulated data, three estimates…
Descriptors: Effect Size, Robustness (Statistics), Simulation, Research Methodology
Moraveji, Behjat; Jafarian, Koorosh – International Journal of Education and Literacy Studies, 2014
The aim of this paper is to provide an introduction of new imputation algorithms for estimating missing values from official statistics in larger data sets of data pre-processing, or outliers. The goal is to propose a new algorithm called IRMI (iterative robust model-based imputation). This algorithm is able to deal with all challenges like…
Descriptors: Mathematics, Computation, Robustness (Statistics), Regression (Statistics)
MacDonald, George T. – ProQuest LLC, 2014
A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…
Descriptors: Simulation, Item Response Theory, Models, Test Items
Zhang, Zhiyong; Lai, Keke; Lu, Zhenqiu; Tong, Xin – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Despite the widespread popularity of growth curve analysis, few studies have investigated robust growth curve models. In this article, the "t" distribution is applied to model heavy-tailed data and contaminated normal data with outliers for growth curve analysis. The derived robust growth curve models are estimated through Bayesian…
Descriptors: Structural Equation Models, Bayesian Statistics, Statistical Inference, Statistical Distributions
Vargha, Andras; Delaney, Harold D. – 2000
In this paper, six statistical tests of stochastic equality are compared with respect to Type I error and power through a Monte Carlo simulation. In the simulation, the skewness and kurtosis levels and the extent of variance heterogeneity of the two parent distributions were varied across a wide range. The sample sizes applied were either small or…
Descriptors: Comparative Analysis, Monte Carlo Methods, Robustness (Statistics), Sample Size
Bonett, Douglas G. – Applied Psychological Measurement, 2006
Comparing variability of test scores across alternate forms, test conditions, or subpopulations is a fundamental problem in psychometrics. A confidence interval for a ratio of standard deviations is proposed that performs as well as the classic method with normal distributions and performs dramatically better with nonnormal distributions. A simple…
Descriptors: Intervals, Mathematical Concepts, Comparative Analysis, Psychometrics

Kirisci, Levent; Hsu, Tse-Chi – 1995
The main goal of this study was to assess how sensitive unidimensional parameter estimates derived from BILOG were when the unidimensionality assumption was violated and the underlying ability distribution was not multivariate normal. A multidimensional three-parameter logistic distribution that was a straightforward generalization of the…
Descriptors: Ability, Comparative Analysis, Correlation, Difficulty Level
Lambert, Richard G.; Curlette, William L. – 1995
Validity generalization meta-analysis (VG) examines the extent to which the validity of an instrument can be transported across settings. VG offers correction and summarization procedures designed in part to remove the effects of statistical artifacts on estimates of association between criterion and predictor. By employing a random effects model,…
Descriptors: Correlation, Error of Measurement, Estimation (Mathematics), Meta Analysis
Nandakumar, Ratna; Yu, Feng – 1994
DIMTEST is a statistical test procedure for assessing essential unidimensionality of binary test item responses. The test statistic T used for testing the null hypothesis of essential unidimensionality is a nonparametric statistic. That is, there is no particular parametric distribution assumed for the underlying ability distribution or for the…
Descriptors: Ability, Content Validity, Correlation, Nonparametric Statistics