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Lawlor, George F. – J Exp Educ, 1970
Descriptors: Colleges, Data Analysis, Institutional Environment
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Degerman, Richard – Psychometrika, 1982
A procedure is described for orienting the nodes of a binary tree to maximize the Kendall rank order correlation (tau) between node order and a given external criterion. The procedure is computationally efficient and is based on application of an ordered set of node tests. (Author)
Descriptors: Cluster Analysis, Correlation, Data Analysis
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Charter, Richard A.; Larsen, Barbara S. – Educational and Psychological Measurement, 1983
While tables and formulas for Fisher's z transformations are commonly included in introductory statistics books, the reverse of this transformation, namely, Fisher's z to r, is not included. Two Fisher's z to r formulas are presented. (Author)
Descriptors: Correlation, Data Analysis, Mathematical Formulas
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Hafner, Robert – Psychometrika, 1981
The method proposed by Harman and Fukuda to treat the so-called Heywood case in the minres method in factor analysis (i.e., the case where the resulting communalities are greater than one) involves the frequent solution of eigenvalue problems. A simple method to treat this problem is presented. (Author/JKS)
Descriptors: Algorithms, Data Analysis, Factor Analysis
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Carithers, Martha W.; Flynn, Cynthia B. – Educational and Psychological Measurement, 1980
Coombs' formulation of Data Quadrants, and Runkle and McGrath's adaptation, were found to be incomplete. The third dichotomy was nonfunctional in half the Quadrants, resulting in inconsistent interpretation of the proximity element. The category "comparison between points and dyads" should be added to complete the logical classification…
Descriptors: Classification, Comparative Analysis, Data Analysis
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Gibson, Nicole Morgan; Olejnik, Stephen – Educational and Psychological Measurement, 2003
Studied the problem of missing data at the second level of a two-level hierarchal data structure using data generated to simulate the 1982 High School and Beyond data set with five different missing data treatments: listwise deletion, overall mean substitution, group mean substitution, the EM algorithm, and multiple imputation. (SLD)
Descriptors: Data Analysis, Longitudinal Studies, Simulation
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Osbourne, Jason W. – Practical Assessment, Research & Evaluation, 2002
Discusses issues involved in data transformation to aid researchers who do not have extensive mathematical backgrounds. Focuses on the use of data transformation for normalization of variables. Emphasizes that researchers should understand their data before performing analyses. (SLD)
Descriptors: Data Analysis, Research Methodology, Researchers
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Ten Berge, Jos M. F. – Multivariate Behavioral Research, 1999
Discusses ipsatizing variables prior to component analysis by subtracting the mean score of each individual from all the scores of that individual, showing technical objections to component analysis of ipsatized variables to be based on erroneous premises. Suggests partialling the mean component as a superior procedure. (SLD)
Descriptors: Data Analysis, Research Methodology, Scores
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Lewin, Alisa C.; Mitchell, Michael N. – Evaluation Review, 1999
Proposes group mean centering as a solution to the problem of pooling data from multiple sites. Uses California's Work Pays Demonstration Project to illustrate three analysis strategies for data from multiple sites. Discusses considerations in choosing the centering strategy. (SLD)
Descriptors: Data Analysis, Evaluation Methods, Experiments
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Sanford, Jon A.; Butterfield, Tina – Gerontologist, 2005
Purpose: Although remote home assessment would enable specialists to prescribe home modifications for anyone, anywhere, the strategy is dependent on the ability to provide specialists with the same information as an in-home assessment. The purpose of this paper is to document that remote assessment is feasible and concurs largely with traditional…
Descriptors: Identification, Data Analysis, Rural Areas
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Mash, Eric J.; Hunsley, John – Journal of Clinical Child and Adolescent Psychology, 2005
The main purpose of this article and this special section is to encourage greater attention to evidence-based assessment (EBA) in the development of a scientifically supported clinical child and adolescent psychology. This increased attention is especially important in light of (a) the omission of assessment considerations in recent efforts to…
Descriptors: Psychometrics, Data Analysis, Student Evaluation
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Poon, Wai-Yin; Wong, Yuen-Kwan – Structural Equation Modeling, 2004
This study uses a Cook's distance type diagnostic statistic to identify unusual observations in a data set that unduly influence the estimation of a covariance matrix. Similar to many other deletion-type diagnostic statistics, this proposed measure is susceptible to masking or swamping effect in the presence of several unusual observations. In…
Descriptors: Statistical Analysis, Data Analysis, Matrices
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von Hippel, Paul T. – Journal of Statistics Education, 2005
Many textbooks teach a rule of thumb stating that the mean is right of the median under right skew, and left of the median under left skew. This rule fails with surprising frequency. It can fail in multimodal distributions, or in distributions where one tail is long but the other is heavy. Most commonly, though, the rule fails in discrete…
Descriptors: Statistical Distributions, Textbooks, Data Analysis
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Joe, Harry; Maydeu-Olivares, Albert – Psychometrika, 2006
In categorical data analysis, two-sample cross-validation is used not only for model selection but also to obtain a realistic impression of the overall predictive effectiveness of the model. The latter is of particular importance in the case of highly parametrized models capable of capturing every idiosyncracy of the calibrating sample. We show…
Descriptors: Data Analysis, Maximum Likelihood Statistics
Oregon Department of Education, 2013
This guide is designed as a reference for District and School personnel working with English learners (ELs). The content of the guide represents a compilation of information, examples, and resources. This guide is a living document and subject to frequent updates. It is recommended to review the document online rather than printing a hard copy.
Descriptors: Program Guides, English Language Learners, Educational Objectives, Vocabulary
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