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Richardson, Alice – Journal of Statistics Education, 2007
The technique of distance sampling is widely used to monitor biological populations. This paper documents an in-class activity to introduce students to the concepts and the mechanics of distance sampling in a simple situation that is relevant to their own experiences. Preparation details are described. Variations and extensions to the activity are…
Descriptors: Sampling, Statistics, Instruction, Biology
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von Davier, Matthias; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2007
Reporting methods used in large-scale assessments such as the National Assessment of Educational Progress (NAEP) rely on latent regression models. To fit the latent regression model using the maximum likelihood estimation technique, multivariate integrals must be evaluated. In the computer program MGROUP used by the Educational Testing Service for…
Descriptors: Simulation, Computer Software, Sampling, Data Analysis
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Ozechowski, Timothy J.; Turner, Charles W.; Hops, Hyman – Psychological Methods, 2007
This article demonstrates the use of mixed-effects logistic regression (MLR) for conducting sequential analyses of binary observational data. MLR is a special case of the mixed-effects logit modeling framework, which may be applied to multicategorical observational data. The MLR approach is motivated in part by G. A. Dagne, G. W. Howe, C. H.…
Descriptors: Probability, Young Adults, Sampling, Observation
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Torgerson, Carole J.; Torgerson, David J. – Educational Studies, 2007
Randomized controlled trials in educational research tend to be small. Small trials can have large, chance, imbalances in important covariates. For studies with sample sizes greater than 50, chance imbalances can be corrected using analysis of covariance; for small trials, however, statistical power is maximized if the trial is balanced and…
Descriptors: Educational Research, Statistical Analysis, Control Groups, Experimental Groups
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Flessner, Christopher A.; Woods, Douglas W.; Franklin, Martin E.; Keuthen, Nancy J.; Piacentini, John; Cashin, Susan E.; Moore, Phoebe S. – Behavior Modification, 2007
This article describes the development and initial psychometric properties of the Milwaukee Inventory for Styles of Trichotillomania-Child Version (MIST-C), a self-report scale designed to assess styles of hair pulling in children and adolescents diagnosed with trichotillomania (TTM). Using Internet sampling procedures, the authors recruited 164…
Descriptors: Measures (Individuals), Psychometrics, Sampling, Factor Analysis
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Estes, Carole; Estes, Gary D. – 1980
Multiple matrix sampling is a sampling design in which both test items and examinees are randomly sampled from their respective populations. This study was designed to develop and assess a method for computing an estimate of a correlation coefficient when a multiple matrix sampling design is used. The examinee populations included 212 third-grade…
Descriptors: Correlation, Elementary Secondary Education, Evaluation Methods, Grade 3
Kier, Frederick J. – 1997
It is a false, but common, belief that statistical significance testing evaluates result replicability. In truth, statistical significance testing reveals nothing about results replicability. Since science is based on replication of results, methods that assess replicability are important. This is particularly true when multivariate methods, which…
Descriptors: Evaluation Methods, Multivariate Analysis, Sampling, Statistical Significance
Roberts, James S.; Wedell, Douglas H.; Laughlin, James E. – 1998
The Likert rating scale procedure is often used in conjunction with a graded disagree-agree response scale to measure attitudes. Item characteristic curves associated with graded disagree-agree responses are generally single-peaked, nonmonotonic functions of true attitude. These characteristics are, thus, more generally consistent with an…
Descriptors: Attitudes, Likert Scales, Sampling, Test Items
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Lutz, J. Gary – Educational and Psychological Measurement, 1974
Descriptors: Computer Programs, Hypothesis Testing, Sampling, Statistical Significance
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Huck, Schuyler W.; Sutton, Cary O. – Journal of Experimental Education, 1974
Considered the statistical comparison of groups under the condition of equal sample sizes. (Author)
Descriptors: Educational Research, Sampling, Statistical Analysis, Tables (Data)
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Barcikowski, Robert S. – Educational and Psychological Measurement, 1974
Descriptors: Error of Measurement, Item Sampling, Testing Problems
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Hubert, Lawrence – Psychometrika, 1974
Descriptors: Factor Structure, Nonparametric Statistics, Sampling, Statistical Analysis
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Joe, George W.; Woodward, J. Arthur – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Matrices, Sampling, Statistical Analysis
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Brookes, B. C. – Journal of Documentation, 1975
A sampling theorem, based on the binomial probability distribution but otherwise distribution-free, is derived and some of its applications are illustrated numerically. (Author)
Descriptors: Information Science, Sampling, Statistical Analysis, Statistical Data
Forsyth, Robert A.; Feldt, Leonard S. – Educ Psychol Meas, 1969
Descriptors: Correlation, Hypothesis Testing, Measurement, Sampling
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