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Neel, John H. – 1987
Determination of statistical power for analysis of variance procedures requires five elements: (1) significance level; (2) effect size; (3) number of means; (4) error variance; and (5) sample size. Significance levels are traditionally chosen to be 0.5, .01, or .001. Effect size is not discussed in this paper. The number of means is determined by…
Descriptors: Analysis of Variance, Error of Measurement, Mathematical Models, Power (Statistics)
Kulick, Edward; Dorans, Neil J. – 1984
A new approach to assessing unexpected differential item performance (item bias or item fairness) is introduced and applied to the item responses of different subpopulations of Scholastic Aptitude Test (SAT) takers. The essential features of the standardization approach are described. The primary goal of the standardization approach is to control…
Descriptors: College Entrance Examinations, Individual Differences, Mathematical Models, Performance Factors
Lautenschlager, Gary J.; Park, Dong-Gun – 1987
The effects of variations in degree of range restriction and different subgroup sample sizes on the validity of several item bias detection procedures based on Item Response Theory (IRT) were investigated in a simulation study. The degree of range restriction for each of two subpopulations was varied by cutting the specified subpopulation ability…
Descriptors: Computer Simulation, Item Analysis, Latent Trait Theory, Mathematical Models
Hwang, Chi-en; Cleary, T. Anne – 1986
The results obtained from two basic types of pre-equatings of tests were compared: the item response theory (IRT) pre-equating and section pre-equating (SPE). The simulated data were generated from a modified three-parameter logistic model with a constant guessing parameter. Responses of two replication samples of 3000 examinees on two 72-item…
Descriptors: Computer Simulation, Equated Scores, Latent Trait Theory, Mathematical Models
McDonald, Roderick P. – 1982
This paper provides an up-to-date review of the relationship between item response theory (IRT) and (nonlinear) common factor theory and draws out of this relationship some implications for current and future research in IRT. Nonlinear common factor analysis yields a natural embodiment of the weak principle of local independence in appropriate…
Descriptors: Factor Analysis, Higher Education, Item Analysis, Latent Trait Theory
Prater, James M., Jr. – 1983
The central purpose of the present study was to evaluate several statistical techniques (analysis of variance (ANOVA) on raw gains, standardized ANOVA, standard analysis of covariance (ANCOVA), and z-score ANOVA) under various quasi-experimental conditions (three levels of reliability, three levels of sample size, three levels of gain, and the…
Descriptors: Achievement Gains, Analysis of Covariance, Analysis of Variance, Computer Simulation
Tucker, Ledyard R.; And Others – 1986
A Monte Carlo study of five indices of dimensionality of binary items used a computer model that allowed sampling of both items and people. Five parameters were systematically varied in a factorial design: (1) number of common factors from one to five; (2) number of items, including 20, 30, 40, and 60; (3) sample sizes of 125 and 500; (4) nearly…
Descriptors: Correlation, Difficulty Level, Educational Research, Expectancy Tables
Sandler, Andrew B. – 1987
Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Discriminant Analysis
Hummel, Thomas J.; Johnston, Charles B. – 1986
This study investigated seven methods for analyzing multivariate group differences. Bonferroni t statistics, multivariate analysis of variance (MANOVA) followed by analysis of variance (ANOVA), and five other methods were studied using Monte Carlo methods. Methods were compared with respect to (1) experimentwise error rate; (2) power; (3) number…
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, Differences
Reckase, Mark D.; Ackerman, Terry A. – 1986
This paper demonstrates the relationship between the concept of unidimensionality and direction of an item in a multidimensional space. The basic premise is that if items that measure in the same direction are combined to form a test, that test will meet the item response theory requirements of unidimensionality. This will be true even if the…
Descriptors: Achievement Tests, College Entrance Examinations, Estimation (Mathematics), Goodness of Fit
Farish, Stephen J. – 1984
The stability of Rasch test item difficulty parameters was investigated under varying conditions. Data were taken from a mathematics achievement test administered to over 2,000 Australian students. The experiments included: (1) relative stability of the Rasch, traditional, and z-item difficulty parameters using different sample sizes and designs;…
Descriptors: Achievement Tests, Difficulty Level, Estimation (Mathematics), Foreign Countries