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Marcus-Roberts, Helen M.; Roberts, Fred S. – Journal of Educational Statistics, 1987
Discusses the controversy over the limits that scales of measurement impose on the statistical procedures on the statistical procedures we may apply, using the measurement-theoretic concept of meaningfulness in the analysis of these limits. (RB)
Descriptors: Error of Measurement, Scaling, Statistics, Validity
Peer reviewed Peer reviewed
Huynh, Huynh – Journal of Educational Statistics, 1981
Simulated data based on five test score distributions indicate that a slight modification of the asymptotic normal theory for the estimation of the p and kappa indices in mastery testing will provide results which are in close agreement with those based on small samples from the beta-binomial distribution. (Author/BW)
Descriptors: Error of Measurement, Mastery Tests, Mathematical Models, Test Reliability
Peer reviewed Peer reviewed
Keselman, H. J.; Keselman, Joanne C. – Journal of Educational Statistics, 1988
Two Tukey multiple comparisons and Bonferroni and multivariate approaches are compared for their rates of Type I error and any-pairs power when multisample sphericity was not satisfied and the design was unbalanced. For tests of weighted means and for study conditions investigated, the Bonferroni procedure provides a workable solution. (TJH)
Descriptors: Error of Measurement, Multivariate Analysis, Power (Statistics), Weighted Scores
Peer reviewed Peer reviewed
Wilcox, Rand R. – Journal of Educational Statistics, 1981
Both the binomial and beta-binomial models are applied to various problems occurring in mental test theory. The paper reviews and critiques these models. The emphasis is on the extensions of the models that have been proposed in recent years, and that might not be familiar to many educators. (Author)
Descriptors: Error of Measurement, Item Analysis, Mathematical Models, Test Reliability
Peer reviewed Peer reviewed
Lord, Frederic M. – Journal of Educational Statistics, 1982
The standard error of an equipercentile equating is derived for four situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data. Standard errors of linear and equipercentile equating are compared. (Author)
Descriptors: Equated Scores, Error of Measurement, Monte Carlo Methods, Test Construction
Peer reviewed Peer reviewed
Hedges, Larry V. – Journal of Educational Statistics, 1981
Glass's estimator of effect size, the sample mean difference divided by the sample standard deviation, is studied in the context of an explicit statistical model. The exact distribution of Glass's estimator is obtained and the estimator is shown to have a small sample bias. Alternatives are proposed and discussed. (Author/JKS)
Descriptors: Data Analysis, Error of Measurement, Mathematical Models, Research Design
Peer reviewed Peer reviewed
Jarjoura, David – Journal of Educational Statistics, 1985
Issues regarding tolerance and confidence intervals are discussed within the context of educational measurement, and conceptual distinctions are drawn between these two types of intervals. Points are raised about the advantages of tolerance intervals when the focus is on a particular observed score rather than a particular examinee. (Author/BW)
Descriptors: Comparative Analysis, Error of Measurement, Mathematical Models, Test Interpretation
Peer reviewed Peer reviewed
Reddon, John R.; And Others – Journal of Educational Statistics, 1985
Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)
Descriptors: Computer Simulation, Correlation, Error of Measurement, Matrices
Peer reviewed Peer reviewed
Tatsuoka, Kikumi, K.; Tatsuoka, Maurice M. – Journal of Educational Statistics, 1982
Two indices for measuring the degree of conformity or consistency of an individual examinee's response pattern on a set of items are developed. The use of the indices for spotting aberrant response patterns of examinees is detailed. (Author/JKS)
Descriptors: Error of Measurement, Error Patterns, Goodness of Fit, Item Analysis
Peer reviewed Peer reviewed
Boodoo, Gwyneth M. – Journal of Educational Statistics, 1982
Incidence sampling is a parsimonious method whereby a large number of examinees can be measured on many variables (such as test items) to assess group characteristics. Parameters used to describe an incidence sample are estimated using the theory of generalized symmetric means and generalizability theory. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Error of Measurement, Measurement Techniques
Peer reviewed Peer reviewed
Zwick, Rebecca – Journal of Educational Statistics, 1990
Use of the Mantel-Haenszel procedure as a test for differential item functioning under the Rasch model of item-response theory is examined. Results of the procedure cannot be generalized to the class of items for which item-response functions are monotonic and local independence holds. (TJH)
Descriptors: Demography, Equations (Mathematics), Error of Measurement, Item Bias
Peer reviewed Peer reviewed
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
Peer reviewed Peer reviewed
Algina, James; Tang, Kezhen L. – Journal of Educational Statistics, 1988
For Y. Yao's and G. S. James' tests, Type I error rates were estimated for various combinations of the number of variables, sample-size and sample-size-to-variables ratios, and heteroscedasticity. These tests are alternatives to Hotelling's T(sup 2) and are intended for use when variance-covariance matrices are unequal for two independent samples.…
Descriptors: Analysis of Covariance, Analysis of Variance, Equations (Mathematics), Error of Measurement
Peer reviewed Peer reviewed
Westermann, Rainer; Hager, Willi – Journal of Educational Statistics, 1986
The well-known problem of cumulating error probabilities is reconsidered from a general epistemological perspective, namely, the concepts of severity and of fairness of tests. It is shown that not only Type 1 but also Type 2 errors can cumulate. A new adjustment strategy is proposed and applied. (Author/JAZ)
Descriptors: Educational Research, Error of Measurement, Hypothesis Testing, Measurement Techniques
Peer reviewed Peer reviewed
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
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