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Myette, Beverly M.; White, Karl R. – 1982
Twenty Monte Carlo studies on multiple comparison (MC) techniques were conducted to examine which MC technique was the "method of choice." The results from these studies had several apparent contradictions when different techniques were investigated under varying sample size and variance conditions. Box's coefficient of variance…
Descriptors: Hypothesis Testing, Sampling, Statistical Analysis, Statistical Bias
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Humphreys, Lloyd G.; Montanelli, Richard G. – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Factor Analysis, Matrices, Sampling
Peer reviewed Peer reviewed
Kaiser, Henry F.; Michael, William B. – Educational and Psychological Measurement, 1975
An alternative derivation of Tryon's basic formula for the coefficient of domain validity or the coefficient of generalizability developed by Cronbach, Rajaratnam, and Glaser is provided. This derivation, which is also the generalized Kuder-Richardson coefficient, requires a relatively minimal number of assumptions compared with that in previously…
Descriptors: Matrices, Sampling, Statistical Analysis, Test Reliability
Kohr, Richard L.; Games, Paul A. – 1974
An empirical sampling study investigated six procedures for testing differences between means in the presence of unequal n's and variances. Support was obtained for previous research which found t robust to heterogeneous variances only when n's are equal and of moderate size. The procedure which emerged as providing the best control over Type I…
Descriptors: Hypothesis Testing, Probability, Sampling, Statistical Analysis
Brown, Bobby R.; Lathrop, Robert L. – 1971
This study investigated the effects of non-normality of the marginal distributions of the bivariate surface upon the sampling distribution of certain tests of significance of differences for the product moment correlation coefficient. The effects of non-normality were found to be rather substantial and to be dependent upon: 1) the degree of…
Descriptors: Correlation, Research Methodology, Sampling, Statistical Analysis
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Sabers, Darrell L.; Klausmeier, Richard D. – Journal of Educational Measurement, 1971
Descriptors: Measurement Techniques, Raw Scores, Sampling, Statistical Analysis
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Geisser, Seymour; Kappenman, Russell F. – Psychometrika, 1971
Descriptors: Bayesian Statistics, Mathematics, Probability, Profiles
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Shoemaker, David M. – Journal of Educational Measurement, 1971
Results indicate that scale values can be approximated satisfactorily through item-examinee sampling. Defining one observation as the response made by one examinee to one item, the similarity between the estimated scale values and normative scale values increased generally with increases in the number of observations acquired by the sampling plan.…
Descriptors: Attitudes, Item Sampling, Norms, Statistical Analysis
Elliot, Brownlee – CEDR Quarterly, 1980
This article presents a fairly quick, easy way to decide what size sample is needed for a survey, given a desired level of confidence and degree of accuracy. The method proposed will work on any multiple response instrument. A technical mathematical explanation is also included. (GK)
Descriptors: Data Collection, Research Design, Sampling, Statistical Analysis
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Dziuban, Charles D.; And Others – Educational and Psychological Measurement, 1979
The distributional characteristics of Kaiser's Measure of Sampling Adequacy (MSA) were investigated in sample matrices generated from multivariate normal populations of specified correlation levels. Systematic variation of sample size and number of variables revealed the overall MSA to be most influenced by the number of variables. (Author/JKS)
Descriptors: Correlation, Factor Analysis, Item Sampling, Psychometrics
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Barchard, Kimberly A.; Hakstian, A. Ralph – Multivariate Behavioral Research, 1997
Two studies, both using Type 12 sampling, are presented in which the effects of violating the assumption of essential parallelism in setting confidence intervals are studied. Results indicate that as long as data manifest properties of essential parallelism, the two methods studied maintain precise Type I error control. (SLD)
Descriptors: Error of Measurement, Robustness (Statistics), Sampling, Statistical Analysis
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Lawrence, Ida M.; Dorans, Neil J. – Applied Measurement in Education, 1990
The sample invariant properties of five anchor test equating methods are addressed. Equating results across two sampling conditions--representative sampling and new-form matched sampling--are compared for Tucker and Levine equally reliable linear equating, item response theory true-score equating, and two equipercentile methods. (SLD)
Descriptors: Equated Scores, Item Response Theory, Sampling, Statistical Analysis
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Alsawalmeh, Yousef M.; Feldt, Leonard S. – Applied Psychological Measurement, 1994
An approximate statistical test of the equality of two intraclass reliability coefficients based on the same sample of people is derived. Such a test is needed when a researcher wishes to compare the reliability of two measurement procedures, and both procedures can be applied to results from the same group. (SLD)
Descriptors: Comparative Analysis, Measurement Techniques, Reliability, Sampling
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Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.; Jiao, Qun G. – Journal of Mixed Methods Research, 2007
A sequential design utilizing identical samples was used to classify mixed methods studies via a two-dimensional model, wherein sampling designs were grouped according to the time orientation of each study's components and the relationship of the qualitative and quantitative samples. A quantitative analysis of 121 studies representing nine fields…
Descriptors: Sampling, Sample Size, Generalization, Qualitative Research
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Braun, Henry; Zhang, Jinming; Vezzu, Sailesh – ETS Research Report Series, 2008
At present, although the percentages of students with disabilities (SDs) and/or students who are English language learners (ELL) excluded from a NAEP administration are reported, no statistical adjustment is made for these excluded students in the calculation of NAEP results. However, the exclusion rates for both SD and ELL students vary…
Descriptors: Research Methodology, Computation, Disabilities, English Language Learners
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