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Kish, Leslie – 1989
A brief, practical overview of "design effects" (DEFFs) is presented for users of the results of sample surveys. The overview is intended to help such users to determine how and when to use DEFFs and to compute them correctly. DEFFs are needed only for inferential statistics, not for descriptive statistics. When the selections for…
Descriptors: Computer Software, Error of Measurement, Mathematical Models, Research Design

Clarkson, Douglas B. – Psychometrika, 1979
The jackknife by groups and modifications of the jackknife by groups are used to estimate standard errors of rotated factor loadings for selected populations in common factor model maximum likelihood factor analysis. Simulations are performed in which t-statistics based upon these jackknife estimates of the standard errors are computed.…
Descriptors: Error of Measurement, Factor Analysis, Factor Structure, Mathematical Models

Kaplan, David – Multivariate Behavioral Research, 1989
The sampling variability and zeta-values of parameter estimates for misspecified structural equation models were examined. A Monte Carlo study was used. Results are discussed in terms of asymptotic theory and the implications for the practice of structural equation models. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Mathematical Models, Monte Carlo Methods

Wilcox, Rand R. – Journal of Educational Statistics, 1990
Recently, C. E. McCulloch (1987) suggested a modification of the Morgan-Pitman test for comparing the variances of two dependent groups. This paper demonstrates that there are situations where the procedure is not robust. A subsample approach, similar to the Box-Scheffe test, and the Sandvik-Olsson procedure are also assessed. (TJH)
Descriptors: Comparative Analysis, Equations (Mathematics), Error of Measurement, Mathematical Models

Wilson, Mark – Journal of Educational Statistics, 1989
An empirical sampling approach was used to assess the accuracy of a Taylor approximation for the estimation of sampling errors. The sampling errors were in the statistics involved in estimating a path model based on medium-sized samples gathered using five sample designs commonly used in educational research. (TJH)
Descriptors: Educational Research, Error of Measurement, Estimation (Mathematics), Mathematical Models

Whitely, Susan E. – Journal of Educational Measurement, 1977
A debate concerning specific issues and the general usefulness of the Rasch latent trait test model is continued. Methods of estimation, necessary sample size, and the applicability of the model are discussed. (JKS)
Descriptors: Error of Measurement, Item Analysis, Mathematical Models, Measurement

Sanders, Piet F. – Psychometrika, 1992
Presents solutions for the problem of maximizing the generalizability coefficient under a budget constraint. Shows that the Cauchy-Schwarz inequality can be applied to derive optimal continuous solutions for the number of conditions of each facet. Illustrates the formal similarity between optimization problems in survey sampling and…
Descriptors: Budgeting, Cost Effectiveness, Equations (Mathematics), Error of Measurement

Wright, Benjamin D. – Journal of Educational Measurement, 1977
Statements made in a previous article of this journal concerning the Rasch latent trait test model are questioned. Methods of estimation, necessary sample sizes, several formuli, and the general usefulness of the Rasch model are discussed. (JKS)
Descriptors: Computers, Error of Measurement, Item Analysis, Mathematical Models

Thompson, Paul A. – Multivariate Behavioral Research, 1991
Application of the bootstrap method to complex psychological analysis is illustrated using a simulation experiment with two populations with small and large samples. The method provides variance estimates, allows testing of nested competing models, and gives a preliminary idea about parameter variability. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Error of Measurement, Estimation (Mathematics)
Reuterberg, Sven-Eric – 1986
This report is about the problem of making transition or enrollment rate gains comparable. It is shown that measures based on the proportions themselves, i.e. the difference between proportions, the proportion ratio and the residual gain ratio do not make the gains comparable. Instead a non-linear transformation has to be done. Two such…
Descriptors: Enrollment, Error of Measurement, Higher Education, Mathematical Models

Kristof, Walter – Psychometrika, 1971
Descriptors: Cognitive Measurement, Error of Measurement, Mathematical Models, Psychological Testing

Berger, Martjin P. F. – Applied Psychological Measurement, 1991
A generalized variance criterion is proposed to measure efficiency in item-response-theory (IRT) models. Heuristic arguments are given to formulate the efficiency of a design in terms of an asymptotic generalized variance criterion. Efficiencies of designs for one-, two-, and three-parameter models are compared. (SLD)
Descriptors: Comparative Analysis, Efficiency, Equations (Mathematics), Error of Measurement
Bump, Wren M. – 1992
An analysis of covariance (ANCOVA) is done to correct for chance differences that occur when subjects are assigned randomly to treatment groups. When properly used, this correction results in adjustment of the group means for pre-existing differences caused by sampling error and reduction of the size of the error variance of the analysis. The…
Descriptors: Analysis of Covariance, Equations (Mathematics), Error of Measurement, Experimental Groups
Kane, Michael T. – 1980
The reliability and validity of measurement is analyzed by a sampling model based on generalizability theory. A model for the relationship between a measurement procedure and an attribute is developed from an analysis of how measurements are used and interpreted in science. The model provides a basis for analyzing the concept of an error of…
Descriptors: Attribution Theory, Behavioral Sciences, Error of Measurement, Mathematical Models
deGruijter, Dato N. M. – 1980
The setting of standards involves subjective value judgments. The inherent arbitrariness of specific standards has been severely criticized by Glass. His antagonists agree that standard setting is a judgmental task but they have pointed out that arbitrariness in the positive sense of serious judgmental decisions is unavoidable. Further, small…
Descriptors: Cutting Scores, Difficulty Level, Error of Measurement, Mastery Tests
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