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Vasu, Ellen Storey – Multiple Linear Regression Viewpoints, 1978
The construction and interpretation of confidence intervals for the prediction of new cases in multiple regression analysis is explained. An example is provided. (JKS)
Descriptors: Computer Programs, Data Analysis, Goodness of Fit, Multiple Regression Analysis
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Bailey, Kent G.; And Others – Journal of Consulting and Clinical Psychology, 1977
Two measures of "breadth" and three measures of "depth" were derived, based on special administration and scoring of the Wechsler Similarities subscale. Factor analyses indicated that breadth and depth can be distinguished statistically, and multiple regression analyses revealed that the derived measures contributed to improved…
Descriptors: Factor Analysis, Intelligence Tests, Multiple Regression Analysis, Predictor Variables
Miller, Douglas E.; Kunce, Joseph T. – Measurement and Evaluation in Guidance, 1973
An empirical study of statistical overkill investigated the generalizability of multiple regression equations as a function of the subject/variable ratio. Data from various-sized groups of rehabilitation clients were used to develop the equations. Findings showed that equations developed on samples with less than a 10 to 1 ratio failed to…
Descriptors: Generalization, Multiple Regression Analysis, Prediction, Predictive Validity
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Schmidt, Frank L. – Educational and Psychological Measurement, 1972
Descriptors: Mathematical Models, Multiple Regression Analysis, Predictor Variables, Psychological Testing
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Borich, Gary D. – Journal of Experimental Education, 1972
Paper reviews the test for regression lines and provides equations for expanding this test to regression planes. (Author)
Descriptors: Analysis of Covariance, Homogeneous Grouping, Mathematical Applications, Multiple Regression Analysis
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Werts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1972
The general problem of using group status to estimate true scores given multiple measures is considered in this paper. (Authors)
Descriptors: Error of Measurement, Group Status, Mathematical Applications, Multiple Regression Analysis
Clark, Robert C.; Timothy, Earl E. – Adult Education, 1972
The objectives of the study was to analyze the socioeconomic and political framework of citizen attitudes influenced by social-psychological factors, and by specific variables such as age, education, and anticipated rise in income. (RB)
Descriptors: Age, Community Attitudes, Community Resources, Educational Background
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Elsner, Gary H. – Journal of Leisure Research, 1971
Descriptors: Economics, Facility Utilization Research, Models, Multiple Regression Analysis
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And Others; Drasgow, Fritz – Applied Psychological Measurement, 1979
A Monte Carlo experiment was used to evaluate four procedures for estimating the population squared cross-validity of a sample least squares regression equation. One estimator was particularly recommended. (Author/BH)
Descriptors: Correlation, Least Squares Statistics, Mathematical Formulas, Multiple Regression Analysis
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Blixt, Sonya L. – Multiple Linear Regression Viewpoints, 1980
The use of multiple regression analysis was compared to the use of discriminant function analysis in the prediction of college faculty rank. The multiple regression technique was shown to be generally superior in this instance. (JKS)
Descriptors: Academic Rank (Professional), College Faculty, Data Analysis, Discriminant Analysis
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McPhee, Robert D.; Seibold, David R. – Human Communication Research, 1979
Offers a brief explication of commonality analysis; a step-by-step discussion of how communication researchers may perform commonality analyses using output from a computer-assisted statistical analysis program; and provides an extended example illustrating a commonality analysis. (JMF)
Descriptors: Analysis of Variance, Communication (Thought Transfer), Communication Research, Multiple Regression Analysis
Suen, Hoi – Journal of Developmental and Remedial Education, 1979
Describes an inductive approach to the evaluation of developmental studies programs using multiple regression analysis to explore variables that contribute to program success. (DR)
Descriptors: Developmental Programs, Evaluation Methods, Higher Education, Multiple Regression Analysis
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Rainer, R. Kelly, Jr.; Miller, Marc D. – Computers in Human Behavior, 1996
Presents the results of multiple regression analysis, test-retest analysis, reliability analysis, exploratory factor analysis, and confirmatory factor analysis of the Computer Attitude Scale in order to assess the instrument's predictive ability, construct validity, and reliability. Findings indicate acceptable characteristics, including stability…
Descriptors: Construct Validity, Evaluation, Factor Analysis, Measures (Individuals)
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Bazargan, Mohsen; Bazargan, Shahrzad; King, Lewis – Gerontologist, 2001
A cross sectional study involving 998 independently living elderly African Americans used the Brief Symptom Inventory to measure paranoid ideation and 14 independent variables including demographic characteristics, cognitive deficit, and depression. Paranoid ideation was found in 10% of the sample. Regression analysis revealed 6 of 14 independent…
Descriptors: Blacks, Depression (Psychology), Emotional Problems, Multiple Regression Analysis
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Choi, Namok – Psychology in the Schools, 2005
Social cognitive theory suggests that self-constructs are better predictors when the specificity levels of self-constructs (as predictors) and the criterion variable closely correspond. In this study it was examined whether self-constructs measured at an intermediate level of specificity better correspond with the criterion variable (course…
Descriptors: Undergraduate Students, Academic Achievement, Self Efficacy, Self Concept
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