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A Comparison of Stepwise Multiple Regression and Hierarchical Multiple Regression


Paper Type 
Opinion
Title 
A Comparison of Stepwise Multiple Regression and Hierarchical Multiple Regression
Author 
Chupensri Wongbuddha and Putipong Bookkamana
Email 
-
Abstract:
The stepwise multiple regression is a method of selecting independent variables (predictor variable) in order to construct the linear relation with the dependent variable (predicted variable). The independent variables, which have high correlation with the dependent variable, will have priority to enter the equation, which is beyond the control of the researcher or theoretical assumptions. Regularly, the researcher will use this method in exploratory research. The hierarchical multiple regression will be used in both exploratory and confirmatory researches. The hierarchical regression can control the independent variables or sets of independent variables entering the regression equation by the consideration of the researcher. Sometimes we use this method by entering the independent variables or sets of independent variables according to the theoretical assumptions. Nevertheless, many researchers use this method to explain the variation of the dependent variable after added the independent variable or sets of the independent variables as well.
Start & End Page 
-
Received Date 
1999-09-29
Revised Date 
Accepted Date 
1999-11-12
Full Text 
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Keyword 
Volume 
Vol.26 No.2 (DECEMBER 1999)
DOI 
SDGs
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Chiang Mai Journal of Science

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