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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
Rasmussen, Jeffrey Lee – Evaluation Review, 1985
A recent study (Blair and Higgins, 1980) indicated a power advantage for the Wilcoxon W Test over student's t-test when calculated from a common mixed-normal sample. Results of the present study indicate that the t-test corrected for outliers shows a superior power curve to the Wilcoxon W.
Descriptors: Computer Simulation, Error of Measurement, Hypothesis Testing, Power (Statistics)
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Algina, James – Multivariate Behavioral Research, 1994
Alternative tests are presented for the between-by-within interaction null hypothesis and for two within-subjects main effects null hypothesis in a split plot design. Estimated Type I error rates for the interaction tests and for several tests of the second null hypothesis are reported. (SLD)
Descriptors: Equations (Mathematics), Error of Measurement, Estimation (Mathematics), Hypothesis Testing
Robey, Randall R.; Barcikowski, Robert S. – 1987
The mixed model analysis of variance assumes a mathematical property known as sphericity. Several preliminary tests have been proposed to detect departures from the sphericity assumption. The logic of the preliminary testing procedure is to conduct the mixed model analysis of variance if the preliminary test suggests that the sphericity assumption…
Descriptors: Analysis of Variance, Error of Measurement, Hypothesis Testing, Mathematical Models
Peer reviewed Peer reviewed
Seaman, Samuel L.; And Others – Journal of Educational Statistics, 1985
For the conditions investigated in the study, the parametric ANCOVA was typically the procedure of choice both as a test of equality of conditional means and as a test of equality of conditional distributions. (Author/LMO)
Descriptors: Analysis of Covariance, Analysis of Variance, Error of Measurement, Hypothesis Testing
Kristof, Walter – 1972
We are concerned with the hypothesis that two variables have a perfect disattenuated correlation, hence measure the same trait except for errors of measurement. This hypothesis is equivalent to saying, within the adopted model, that true scores of two psychological tests satisfy a linear relation. A statistical test of this hypothesis is derived…
Descriptors: Correlation, Error of Measurement, Factor Analysis, Hypothesis Testing
Peer reviewed Peer reviewed
Neale, Michael C.; And Others – Multivariate Behavioral Research, 1994
In studies of relatives, conventional multiple regression may not be appropriate because observations are not independent. Obtaining estimates of regression coefficients and correct standard errors from these populations through a structural equation modeling framework is discussed and illustrated with data from twins. (SLD)
Descriptors: Analysis of Covariance, Causal Models, Data Collection, Error of Measurement
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
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1985
The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Assisted Testing, Computer Software