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Collier, Raymond O., Jr.; Larson, Robert C. – Rev Educ Res, 1969
Descriptors: Monte Carlo Methods, Probability, Sampling, Statistics
Peer reviewedHillestad, Mildren – Business Education Forum, 1972
Descriptors: Business Education, Research, Research Methodology, Sampling
Peer reviewedKaiser, Henry F. – Educational and Psychological Measurement, 1981
A revised version of Kaiser's Measure of Sampling Adequacy for factor-analytic data matrices is presented. (Author)
Descriptors: Correlation, Factor Analysis, Research Problems, Sampling
McKenzie, Leon – Perspectives in Adult Learning and Development, 1981
Presents a formula for the determination of sample size in survey research and methods for its manipulation in relation to (1) the nature of the problem; (2) the homogeneity of the population; (3) the desired degree of precision; and (4) allowable costs. (Journal availability: Department of Adult Education, Kansas State University, Manhattan, KS…
Descriptors: Adult Education, Educational Research, Sampling, Surveys
Hinrichs, John R. – Personnel, 1976
The work-sampling approach derives a composite overall picture of how an individual allocates time by taking a sufficiently large number of spot observations of activity at random intervals. (For availability, see EA 507 433.) (Author)
Descriptors: Administrators, Data Collection, Efficiency, Productivity
Peer reviewedMartin, Charles G. – Psychometrika, 1976
The Box-Scheffe and Z-Variance tests for homogeneity of variance are discussed and compared in light of a previous comparison in the literature. Alternative statistics to these tests are discussed and a table comparing the power of the tests is provided. (JKS)
Descriptors: Analysis of Variance, Power (Statistics), Sampling
Peer reviewedLevy, Kenneth J. – Educational and Psychological Measurement, 1977
Bechhofer's procedure for selecting the population with the largest mean from among several populations with known variances is discussed as it applies to the problem of selecting the bivariate normal population with the largest correlation coefficient. Tables of appropriate sample sizes are provided and an example is discussed. (Author/JKS)
Descriptors: Correlation, Research Design, Sampling, Tables (Data)
Peer reviewedYung, Yiu-Fai – Psychometrika, 1997
Various types of finite mixtures of confirmatory factor analysis models are proposed for handling data heterogeneity. Proposed classes of mixture models differ in their unique representations of data heterogeneity, and three sampling schemes for these mixtures are distinguished. Advantages of the Approximate Scoring method are outlined. (SLD)
Descriptors: Data Analysis, Mathematical Models, Sampling, Scoring
Peer reviewedKane, Michael – Journal of Educational Measurement, 2002
Reviews the criticisms of sampling assumptions in generalizability theory (and in reliability theory) and examines the feasibility of using representative sampling, stratification, homogeneity assumptions, and replications to address these criticisms. Suggests some general outlines for the conduct of generalizability theory studies. (SLD)
Descriptors: Generalizability Theory, Reliability, Research Methodology, Sampling
Peer reviewedKalleberg, Arne L.; And Others – Administrative Science Quarterly, 1990
Compares costs and effectiveness of five organizational sampling frames (direct enumeration, unemployment insurance (UI) forms, Dun and Bradstreet's Market Identifier (DMI) files, telephone directory white pages, and chamber of commerce membership directories) at identifying a population of business organizations in Durham County, North Carolina.…
Descriptors: Cost Effectiveness, Research Methodology, Sampling, Surveys
Peer reviewedLambert, Zarrel V.; And Others – Educational and Psychological Measurement, 1990
Use of the bootstrap method to approximate the sampling variation of eigenvalues is explicated, and its usefulness is amplified by an illustration in conjunction with two commonly used factor criteria. These criteria are eigenvalues larger than one and the Scree test. (TJH)
Descriptors: Evaluation Criteria, Factor Analysis, Matrices, Sampling
Peer reviewedAlgina, James; Hombo, Catherine M. – Educational and Psychological Measurement, 1998
The Statistical Analysis System (SAS) has been used to program power calculations for the independent samples Hotellings T squared. Three programs have been prepared to accommodate variations in the information that may be available to do the power analysis. (Author/SLD)
Descriptors: Computer Oriented Programs, Power (Statistics), Sampling
Peer reviewedHakstian, A. Ralph; Barchard, Kimberly A. – Multivariate Behavioral Research, 2000
Developed a sample-based nonanalytical degrees-of-freedom correction factor for situations sampling both subjects and conditions with measurement data departing from essentially parallel form. Assessed the application of this correction factor through a simulation study involving data sets with a range of design characteristics and manifesting…
Descriptors: Robustness (Statistics), Sampling, Simulation, Statistical Inference
Peer reviewedVacha-Haase, Tammi; Kogan, Lori R.; Thompson, Bruce – Educational and Psychological Measurement, 2000
Investigated how dissimilar in composition and variability samples inducting reliability coefficients from prior studies were from the cited prior samples from which coefficients were generalized. Results from 20 articles show that citing reliability coefficients from prior studies as the basis for concluding new scores are reliable is only…
Descriptors: Reliability, Sampling, Scores, Test Manuals
Peer reviewedRaykov, Tenko – Multivariate Behavioral Research, 1997
The population discrepancy between Cronbach's Coefficient Alpha (L. Cronbach, 1951) and scale reliability with fixed congeneric measure, uncorrelated errors, and sampling of subjects was studied. The difference is expressed in terms of the individual component violations of the assumption of equal tau-equivalence that is necessary and sufficient…
Descriptors: Error of Measurement, Reliability, Sampling, Scaling


