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Moy, Mabel L. Y.; Barcikowski, Robert S. – 1973
Using a computer-based Monte Carlo approach to generate item responses, the results of this study indicate that, when item discrimination indices are considered, item-examinee sampling procedures having the same number of observations have different standard errors in estimating both test mean and test variance. With certain types of tests, a…
Descriptors: Error of Measurement, Evaluation Methods, Item Sampling, Monte Carlo Methods
Peer reviewedMoy, Mabel L. Y.; Barcikowski, Robert S. – Journal of Experimental Education, 1974
The purpose of this study was to help determine optimum item sampling plans for use in school evaluation projects. (Author)
Descriptors: Data Analysis, Evaluation Methods, Guidelines, Item Sampling
Peer reviewedFhaner, Stig – Scandinavian Journal of Educational Research, 1973
An item sampling model for achievement testing with items scored in an arbitrary number of categories is investigated. (Author)
Descriptors: Achievement Tests, Decision Making, Item Sampling, Models
Shrestha, Gambhir M.; And Others – 1972
The second section of a four-part technical report of Florida's statewide program for assessing reading-related skills in grades 2 and 4 provides statistical and scoring information. Item and student sampling, a test re-scoring study, reporting statewide assessment data (percentage of achievement, types of tables used), and standard error…
Descriptors: Evaluation Methods, Grade 2, Grade 4, Item Sampling
Peer reviewedKaiser, Henry F.; Hunka, Steve – Educational and Psychological Measurement, 1973
Authors conclude that, in the world of real data sample correlation matrices, Guttman's stronger lower bound is not of practical use in determining the effective number of common factors. (Authors/CB)
Descriptors: Factor Analysis, Factor Structure, Item Sampling, Mathematical Applications
Peer reviewedMacready, George B.; Merwin, Jack C. – Educational and Psychological Measurement, 1973
In this paper consideration is given to the nature of the relationships among items within item forms and how these relationships compare with an ideal case for diagnostic tests in which if a person gets one item within an item form right then he would get all items within the item form correct. (Authors)
Descriptors: Criterion Referenced Tests, Diagnostic Tests, Homogeneous Grouping, Item Analysis
Peer reviewedShoemaker, David M. – Journal of Educational Measurement, 1973
Investigated empirically through post mortem item-examinee samplings were the relative merits of two alternative procedures for allocating items to subtests in multiple matrix sampling and the feasibility of using the jackknife in approximating standard errors of estimate. (Editor)
Descriptors: Databases, Error of Measurement, Item Sampling, Research Design
Peer reviewedShoemaker, David M. – Educational and Psychological Measurement, 1972
Descriptors: Difficulty Level, Error of Measurement, Item Sampling, Simulation
Peer reviewedGross, Alan L. – Psychometrika, 1973
Expressions for the expected value, density, and distribution function (DF) of GS (gain from selection) are derived and studied in terms of sample size, number of predictors, and the prior distribution assigned to the population multiple correlation. (Author/RK)
Descriptors: Academic Achievement, College Admission, Item Sampling, Predictive Measurement
Peer reviewedBarcikowski, Robert S. – Journal of Educational Measurement, 1972
These results indicate that in deciding on the data-gathering design to be used in seeking norm information, attention should be given to item characteristics and test length with particular attention paid to the range of biserial correlations between item response and ability. (Author)
Descriptors: Item Sampling, Mathematical Models, Measurement Techniques, Monte Carlo Methods
Peer reviewedBunda, Mary Anne – Journal of Educational Measurement, 1973
Procedures to be applicable in situations in which large numbers of individuals are tested or in situations where multiple measures are taken. (Author/CB)
Descriptors: Data Collection, Group Norms, Individual Testing, Item Sampling
Peer reviewedScott, William A. – Educational and Psychological Measurement, 1972
Descriptors: Item Sampling, Mathematical Applications, Scoring Formulas, Statistical Analysis
Peer reviewedReilly, 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 reviewedTucker, Ledyard R.; Lewis, Charles – Psychometrika, 1973
Maximum likelihood factor analysis provides an effective method for estimation of factor matrices and a useful test statistic in the likelihood ratio for rejection of overly simple factor models. A reliability coefficient is proposed for analysis of factor solution. (Author/RK)
Descriptors: Analysis of Variance, Factor Analysis, Goodness of Fit, Item Sampling
Peer reviewedClaudy, John G. – Educational and Psychological Measurement, 1972
First purpose of this study was to investigate empirically the accuracy of prediction using regression weights selected through the use of variance-reduction procedures. (Author)
Descriptors: Comparative Analysis, Error Patterns, Factor Structure, Item Sampling
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