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Subkoviak, Michael J. – 1976
A number of different definitions and indices of reliability for mastery tests have recently been proposed in an attempt to cope with possible lack of score variability that attenuates traditional coefficients. One promising index that has been suggested is the proportion of students in a group that are consistently assigned to the same mastery…
Descriptors: Criterion Referenced Tests, Mastery Tests, Mathematical Models, Scores
Marshall, J. Laird; Serlin, Ronald C. – 1979
Four recent indices emphasizing the interrelationships of score distribution shape, modality, mean, and variance were investigated to determine the reliability of mastery tests. Attention was focused on the values of the indices when the cutoff score was near to or far from the modes of distribution. Five types of score distributions were…
Descriptors: Cutting Scores, Mastery Tests, Mathematical Formulas, Mathematical Models

Zimmerman, Donald W.; And Others – Educational and Psychological Measurement, 1993
Coefficient alpha was examined through computer simulation as an estimate of test reliability under violation of two assumptions. Coefficient alpha underestimated reliability under violation of the assumption of essential tau-equivalence of subtest scores and overestimated it under violation of the assumption of uncorrelated subtest error scores.…
Descriptors: Computer Simulation, Estimation (Mathematics), Mathematical Models, Robustness (Statistics)

Zimmerman, Donald W.; And Others – Journal of Experimental Education, 1981
Reliability coefficients of linear combinations of observed scores have anomalous properties which have led to difficulties in the investigation of difference scores and gain scores in test theory. Discrepancies between classical results and correct results obtained from more general formulas, which allow for correlated errors, are examined…
Descriptors: Error of Measurement, Mathematical Formulas, Mathematical Models, Scores

Levin, Joseph – Multivariate Behavioral Research, 1986
The relation between the power of a significance test in a block design with correlated measurements and the reliability of the measuring instrument is analyzed in terms of the components of variance entering the reliability coefficient and the noncentrality parameter. (Author/LMO)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Power (Statistics)

Reuterberg, Sven-Eric; Gustafsson, Jan-Eric – Educational and Psychological Measurement, 1992
The use of confirmatory factor analysis by the LISREL program is demonstrated as an assumption-testing method when computing reliability coefficients under different model assumptions. Results indicate that reliability estimates are robust against departure from the assumption of parallelism of test items. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Mathematical Models, Robustness (Statistics)

Knott, M.; Bartholomew, D. J. – Psychometrika, 1993
Scoring of response vectors to give maximum test-retest correlation is investigated. A general method is given for finding the best scores, deriving them for the normal factor model, and showing that for a standard model for binary response it is easy to approximate the best scores. (SLD)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Mathematical Models

Lam, Tony C. M. – 1981
The objective of this paper is to examine the relationship between the unreliability of difference scores and the power of tests of significance in an attempt to determine the validity of the paradox for the measurement of change presented by Overall and Woodward: that the power of tests of significance is maximum when the reliability of the…
Descriptors: Achievement Gains, Correlation, Error of Measurement, Hypothesis Testing

Rentz, R. Robert – Educational and Psychological Measurement, 1980
This paper elaborates on the work of Cardinet, and others, by clarifying some points regarding calculations, specifically with reference to existing computer programs, and by presenting illustrative examples of the calculation and interpretation of several generalizability coefficients from a complex six-facet (factor) design. (Author/RL)
Descriptors: Analysis of Variance, Computation, Computer Programs, Error of Measurement
Linacre, John M. – 1993
Generalizability theory (G-theory) and many-facet Rasch measurement (Rasch) manage the variability inherent when raters rate examinees on test items. The purpose of G-theory is to estimate test reliability in a raw score metric. Unadjusted examinee raw scores are reported as measures. A variance component is estimated for the examinee…
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Evaluators

Cahan, Sorel – Educational and Psychological Measurement, 1989
Statistical significance and "abnormality" have been used as criteria for the evaluation of intra-individual subtest score differences. Shortcomings of these criteria are identified, and improved estimates of the true score differences are suggested. The applicability of the abnormality criterion to these improved estimates is reviewed.…
Descriptors: Estimation (Mathematics), Evaluation Methods, Individual Differences, Mathematical Models
Goldstein, Harvey; Ecob, Russell – 1981
Using data from a National Child Development Study (NCDS) in Great Britain, the applications of instrumental variable methods and structural equation models to estimating instrumental variables are presented. A subset of the longitudinal educational and home background data on children born in England, Wales and Scotland in a March week of 1958 is…
Descriptors: Analysis of Variance, Elementary Secondary Education, Error of Measurement, Longitudinal Studies

Hakstian, A. Ralph; And Others – Psychometrika, 1988
A model and computation procedure based on classical test score theory are presented for determination of a correlation coefficient corrected for attenuation due to unreliability. Delta and Monte Carlo method applications are discussed. A power analysis revealed no serious loss in efficiency resulting from correction for attentuation. (TJH)
Descriptors: Correlation, Equations (Mathematics), Hypothesis Testing, Mathematical Models

Holland, Paul W.; Wainer, Howard – Applied Measurement in Education, 1990
Two attempts to adjust state mean Scholastic Aptitude Test (SAT) scores for differential participation rates are examined. Both attempts are rejected, and five rules for performing adjustments are outlined to foster follow-up checks on untested assumptions. National Assessment of Educational Progress state data are determined to be more accurate.…
Descriptors: College Applicants, College Entrance Examinations, Estimation (Mathematics), Item Bias

Harvill, Leo M. – Educational Measurement: Issues and Practice, 1991
This paper discusses standard error of measurement (SEM), the amount of variation or spread in the measurement errors for a test, and gives information needed to interpret test scores using SEMs. SEMs at various score levels should be used in calculating score bands rather than a single SEM value. (SLD)
Descriptors: Definitions, Equations (Mathematics), Error of Measurement, Estimation (Mathematics)
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