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Subkoviak, Michael J.; Levin, Joel R. – Journal of Educational Measurement, 1977
Measurement error in dependent variables reduces the power of statistical tests to detect mean differences of specified magnitude. Procedures for determining power and sample size that consider the reliability of the dependent variable are discussed and illustrated. Methods for estimating reliability coefficients used in these procedures are…
Descriptors: Error of Measurement, Hypothesis Testing, Power (Statistics), Sampling
Peer reviewed Peer reviewed
Callender, John C.; Osburn, H. G. – Journal of Educational Measurement, 1979
Some procedures for estimating internal consistency reliability may be superior mathematically to the more commonly used methods such as Coefficient Alpha. One problem is computational difficulty; the other is the possibility of overestimation due to capitalization on chance. (Author/CTM)
Descriptors: Higher Education, Mathematical Formulas, Research Problems, Sampling
Peer reviewed Peer reviewed
Garg, Rashmi; And Others – Journal of Educational Measurement, 1986
For the purpose of obtaining data to use in test development, multiple matrix sampling plans were compared to examinee sampling plans. Data were simulated for examinees, sampled from a population with a normal distribution of ability, responding to items selected from an item universe. (Author/LMO)
Descriptors: Difficulty Level, Monte Carlo Methods, Sampling, Statistical Studies
Peer reviewed Peer reviewed
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
Peer reviewed Peer reviewed
Frisbee, David A. – Journal of Educational Measurement, 1973
The purpose of this study was to gather empirical evidence to compare the reliabilities and concurrent validities of multiple choice and true-false tests that were written to measure understandings and relationships in the same content areas. (Author)
Descriptors: Achievement Tests, Correlation, High School Students, Measurement
Peer reviewed Peer reviewed
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
Peer reviewed Peer reviewed
Reilly, Richard R.; Jackson, Rex – Journal of Educational Measurement, 1973
The present study suggests that although the reliability of an academic aptitude test given under formula-score condition can be increased substantially through empirical option weighting, much of the increase is due to the capitalization of the keying procedure on omitting tendencies which are reliable but not valid. (Author)
Descriptors: Aptitude Tests, Correlation, Factor Analysis, Item Sampling
Peer reviewed Peer reviewed
Askegaard, Lewis D.; Umila, Benwardo V. – Journal of Educational Measurement, 1982
Multiple matrix sampling of items and examinees was applied to an 18-item rank order instrument administered to a randomly assigned group and compared to the ordering and ranking of all items by control subjects. High correlations between ranks suggest the methodology may viably reduce respondent effort on long rank ordering tasks. (Author/CM)
Descriptors: Evaluation Methods, Item Sampling, Junior High Schools, Student Reaction
Peer reviewed Peer reviewed
Kolen, Michael J.; Whitney, Douglas R. – Journal of Educational Measurement, 1982
The adequacy of equipercentile, linear, one-parameter (Rasch), and three-parameter logistic item-response theory procedures for equating 12 forms of five tests of general educational development were compared. Results indicated the equating method adequacy depends on a variety of factors such as test characteristics, equating design, and sample…
Descriptors: Achievement Tests, Comparative Analysis, Equated Scores, Equivalency Tests