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O'Grady, Kevin E.; Medoff, Deborah R. – Multivariate Behavioral Research, 1988
Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)
Descriptors: Multiple Regression Analysis, Predictive Measurement, Regression (Statistics), Research Problems
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Gibbons, James A.; Sherwood, Robert D. – Educational and Psychological Measurement, 1985
This article reviews some of the properties of criterion-scaled regression analysis, especially as it relates to the analysis of a repeated measures/randomized block design. (Author/LMO)
Descriptors: Analysis of Variance, Correlation, Multiple Regression Analysis, Statistical Studies
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Windle, Michael; Lerner, Richard M. – Merrill-Palmer Quarterly, 1984
Among 153 young adult dating dyads, predictions were tested that were derived from a goodness of fit model of the role of temperament in person-social context relations, and from the related filtering/similarity hypothesis. Measured were each dyad member's temperament and expectations for partner's temperament. Results indicated a significant…
Descriptors: College Students, Dating (Social), Expectation, Multiple Regression Analysis
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Green, Bert F. Jr. – Psychometrika, 1976
A summary and interpretation of the recent literature on the indeterminancy of factor scores is given in simple terms. A good index of factor score determinancy is the squared multiple correlation of the factor with the observed variables. (Author)
Descriptors: Correlation, Factor Analysis, Factor Structure, Multiple Regression Analysis
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Grobe, Cary H. – Journal of Research in Science Teaching, 1973
A study to demonstrate the use of multiple regression for evaluation of instructional strategies in science. Two groups of students received Audio-Tutorial and conventional instruction. Research design was a treatment by levels with two treatments and three levels of aptitude within each treatment. (PS)
Descriptors: Multiple Regression Analysis, Research Methodology, Science Education, Statistical Analysis
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Furby, Lita – Developmental Psychology, 1973
Purpose of this article is to explain the fundamental nature and sources of regression toward the mean. The ultimate goal is that developmental psychologists understand regression effects well enough so that they will not make erroneous interpretations of such effects in their empirical data. (Author)
Descriptors: Developmental Psychology, Error of Measurement, Measurement, Multiple Regression Analysis
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Granzin, Kent L.; Painter, John J. – American Educational Research Journal, 1973
Authors discovered significant correlations between couse ratings and variables representing commitment and course-end attitudes toward the course; conclusions suggested steps an instructor might take to improve his ratings.'' (Authors)
Descriptors: Course Evaluation, Multiple Regression Analysis, Predictive Validity, Predictor Variables
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Bolton, Brian – Rehabilitation Research and Practice Review, 1972
Descriptors: Comparative Analysis, Multiple Regression Analysis, Predictive Validity, Predictor Variables
Williams, John D.; Lindem, Alfred C. – College of Education Record (University of North Dakota), 1971
The authors describe a computer program which deals with sets of variables rather than with one variable at a time. (MM)
Descriptors: Computer Programs, Data Analysis, Educational Research, Multiple Regression Analysis
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Corazzini, Arthur J.; And Others – Journal of Human Resources, 1972
Descriptors: Educational Demand, Enrollment Influences, Higher Education, Multiple Regression Analysis
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Werts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1971
Descriptors: Analysis of Covariance, Analysis of Variance, Mathematical Models, Multiple Regression Analysis
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Cudeck, Robert; Browne, Michael W. – Multivariate Behavioral Research, 1983
Methods for comparing the suitability of alternative models for covariance matrices are examined. A cross-validation procedure is suggested and its properties examined. A series of examples using longitudinal data are examined. (Author/JKS)
Descriptors: Correlation, Data Analysis, Multiple Regression Analysis, Multivariate Analysis
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Camp, Cameron J.; Maxwell, Scott E. – Journal of Gerontology, 1983
Compared six effect size (ES) measures commonly used by gerontological researchers as these measures relate to one another in both the analysis of variance and multiple regression models. Also discusses three other issues involving ES measures: the ES of a contrast; orthogonal and nonorthogonal designs; and partial ESs. (Author/JAC)
Descriptors: Analysis of Variance, Comparative Testing, Gerontology, Multiple Regression Analysis
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Steer, Robert A.; And Others – Journal of Clinical Psychology, 1983
Assesses levels of depression presented by 76 male and 29 female alcoholics using Beck Depression Inventory and Hamilton Psychiatric Rating Scale for Depression. To estimate overall depression from the self-report and clinical instruments, Z scores for both measures were summed. Correlations were calculated between composite scores and alcoholics'…
Descriptors: Alcoholism, Clinical Diagnosis, Depression (Psychology), Females
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Judd, Charles M.; Kenny, David A. – Evaluation Review, 1981
Rationale and procedures for conducting process analysis in evaluation research are discussed. Two different procedures for estimating mediation are discussed, as well as procedures for examining whether a treatment exerts its effects, in part, by altering mediating process that produces outcome. Benefits of process analysis in evaluation research…
Descriptors: Control Groups, Experimental Groups, Maximum Likelihood Statistics, Models
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