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Weitzman, R. A. – Journal of Educational and Behavioral Statistics, 2006
Focusing on a single sample obtained randomly with replacement from a single population, this article examines the regression of population on sample proportions and develops an unbiased estimator of the square of the correlation between them. This estimator turns out to be the regression coefficient. Use of the squared-correlation estimator as a…
Descriptors: Sample Size, Intervals, Credibility, Computation
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Algina, James; Olejnik, Stephen – Multivariate Behavioral Research, 2003
Tables for selecting sample size in correlation studies are presented. Some of the tables allow selection of sample size so that r (or r[squared], depending on the statistic the researcher plans to interpret) will be within a target interval around the population parameter with probability 0.95. The intervals are [plus or minus] 0.05, [plus or…
Descriptors: Probability, Intervals, Sample Size, Multiple Regression Analysis
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Weng, Li-Jen; Cheng, Chung-Ping – Educational and Psychological Measurement, 2005
The present simulation investigated the performance of parallel analysis for unidimensional binary data. Single-factor models with 8 and 20 indicators were examined, and sample size (50, 100, 200, 500, and 1,000), factor loading (.45, .70, and .90), response ratio on two categories (50/50, 60/40, 70/30, 80/20, and 90/10), and types of correlation…
Descriptors: Correlation, Sample Size, Data Analysis, Factor Analysis
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Chen, Fang Fang; West, Stephen G.; Sousa, Karen H. – Multivariate Behavioral Research, 2006
Bifactor and second-order factor models are two alternative approaches for representing general constructs comprised of several highly related domains. Bifactor and second-order models were compared using a quality of life data set (N = 403). The bifactor model identified three, rather than the hypothesized four, domain specific factors beyond the…
Descriptors: Quality of Life, Models, Sample Size, Factor Analysis
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Fan, Xitao; Fan, Xiaotao – Journal of Experimental Education, 2005
The authors investigated 2 issues concerning the power of latent growth modeling (LGM) in detecting linear growth: the effect of the number of repeated measurements on LGM's power in detecting linear growth and the comparison between LGM and some other approaches in terms of power for detecting linear growth. A Monte Carlo simulation design was…
Descriptors: Statistical Analysis, Sample Size, Monte Carlo Methods, Structural Equation Models
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Kowalchuk, Rhonda K.; Keselman, H. J.; Algina, James; Wolfinger, Russell D. – Educational and Psychological Measurement, 2004
One approach to the analysis of repeated measures data allows researchers to model the covariance structure of their data rather than presume a certain structure, as is the case with conventional univariate and multivariate test statistics. This mixed-model approach, available through SAS PROC MIXED, was compared to a Welch-James type statistic.…
Descriptors: Interaction, Sample Size, Statistical Analysis, Evaluation Methods
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Fidalgo, Angel M.; Ferreres, Doris; Muniz, Jose – Educational and Psychological Measurement, 2004
Sample-size restrictions limit the contingency table approaches based on asymptotic distributions, such as the Mantel-Haenszel (MH) procedure, for detecting differential item functioning (DIF) in many practical applications. Within this framework, the present study investigated the power and Type I error performance of empirical and inferential…
Descriptors: Test Bias, Evaluation Methods, Sample Size, Error Patterns
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Blitstein, Jonathan L.; Murray, David M.; Hannan, Peter J.; Shadish, William R. – Evaluation Review, 2005
This article builds on the previous article by Blitstein et al. (2005), which showed how external estimates of intraclass correlation can be used to improve the precision for the analysis of an existing group randomized trial. The authors extend that work to sample size estimation and power analysis for future group-randomized trials. Often this…
Descriptors: Statistical Analysis, Regression (Statistics), Sample Size, Correlation
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Skaggs, Gary – Journal of Educational Measurement, 2005
This study investigated the effectiveness of equating with very small samples using the random groups design. Of particular interest was equating accuracy at specific scores where performance standards might be set. Two sets of simulations were carried out, one in which the two forms were identical and one in which they differed by a tenth of a…
Descriptors: Equated Scores, Simulation, Performance Based Assessment, Evaluation Methods
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Christensen, Karl Bang; Kreiner, Svend – Applied Psychological Measurement, 2007
Many statistical tests are designed to test the different assumptions of the Rasch model, but only few are directed at detecting multidimensionality. The Martin-Lof test is an attractive approach, the disadvantage being that its null distribution deviates strongly from the asymptotic chi-square distribution for most realistic sample sizes. A Monte…
Descriptors: Item Response Theory, Monte Carlo Methods, Testing, Models
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Monahan, Patrick O.; Stump, Timothy E.; Finch, Holmes; Hambleton, Ronald K. – Applied Psychological Measurement, 2007
DETECT is a nonparametric "full" dimensionality assessment procedure that clusters dichotomously scored items into dimensions and provides a DETECT index of magnitude of multidimensionality. Four factors (test length, sample size, item response theory [IRT] model, and DETECT index) were manipulated in a Monte Carlo study of bias, standard error,…
Descriptors: Test Length, Sample Size, Monte Carlo Methods, Geometric Concepts
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Nylund, Karen L.; Asparouhov, Tihomir; Muthen, Bengt O. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study…
Descriptors: Test Items, Monte Carlo Methods, Program Effectiveness, Data Analysis
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Liu, Leping; Aberasturi, Suzanne M.; Axtell, Kulwadee; Richmond, Aaron – Computers in the Schools, 2007
Publication bias refers to a tendency to publish articles with significant results over publications with nonsignificant results. In this article we first review the literature of publication bias focusing on the three major determinants (file drawer significance, file drawer effect size, and file drawer sample size) and two interrelated sources…
Descriptors: Sample Size, Information Technology, Periodicals, Effect Size
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Kahveci, Murat – Educational Technology & Society, 2007
Although there is no agreement as to what instructional interactivity and interaction mean in educational literature, researchers agree that both terms are vital for teaching and learning one way or another. This paper presents the item-development stages and validity and reliability analyses of the Interactivity Survey (IS), which attempts to…
Descriptors: Test Results, Internet, Validity, Reliability
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Thorpe, Andy; Snell, Martin; Hoskins, Sherria; Bryant, Janet – Higher Education Quarterly, 2007
A central tenet of contemporary education policy relates to the desire to extend higher education (HE) provision to less advantaged groups ("widening participation"). Our paper contends that a key behavioural obstacle to widening participation lies in the erroneous belief that persists among potential entrants from disadvantaged…
Descriptors: Self Concept, College Freshmen, Higher Education, Educational Policy
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