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The Effects of the Ratio of Utilized Predictors to Original Predictors on the Shrinkage of Multiple Correlation Coefficients (open access)

The Effects of the Ratio of Utilized Predictors to Original Predictors on the Shrinkage of Multiple Correlation Coefficients

This study dealt with shrinkage in multiple correlation coefficients computed for sample data when these coefficients are compared to the multiple correlation coefficients for populations and the effect of the ratio of utilized predictors to original predictors on the shrinkage in R square. The study sought to provide the rationale for selection of the shrinkage formula when the correlations between the predictors and the criterion are known and determine which of the three shrinkage formulas (Browne, Darlington, or Wherry) will yield the R square from sample data that is closest to the R square for the population data.
Date: August 1983
Creator: Petcharat, Prataung Parn
System: The UNT Digital Library
Short-to-Medium Term Enrollment Projection Based on Cycle Regression Analysis (open access)

Short-to-Medium Term Enrollment Projection Based on Cycle Regression Analysis

Short-to-medium projections were made of student semester credit hour enrollments for North Texas State University and the Texas Public and Senior Colleges and Universities (as defined by the Coordinating Board, Texas College and University System). Undergraduate, Graduate, Doctorate, Total, Education, Liberal Arts, and Business enrollments were projected. Fall + Spring, Fall, Summer I + Summer II, Summer I were time periods for which projections were made. A new regression analysis called "cycle regression" which employs nonlinear regression techniques to extract multifrequential phenomena from time-series data was employed for the analysis of the enrollment data. The heuristic steps employed in cycle regression analysis are similar to those used in fitting polynomial models. A trend line and one or more sin waves (cycles) are simultaneously estimated using a partial F test. The process of adding cycle(s) to the model continues until no more significant terms can be estimated.
Date: August 1983
Creator: Chizari, Mohammad
System: The UNT Digital Library