Paper Search
Main Menu
Homepage
Submission
Papers In Press
Search
Information for Contributors
Introducing the Journal
Board of Journal of Science
Contact address
 
Select by Volumes


 
 
 
 
 
 
 
SCImago Journal & Country Rank
 
0.39
2018CiteScore
 
25th percentile
Powered by  Scopus
Home > A Comparison of Stepwise Multiple Regression and Hierarchical Multiple Regression
 
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
Accepted Date
1999-11-12
Full Text
None
Correspondence:
Author Name
Chupensri Wongbuddha - Research Unit of Environment and Technology, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand.
Putipong Bookkamana - Research Unit of Environment and Technology, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand.
Keyword:
Keyword
Volume
Vol.26 No.2 (DECEMBER 1999)
 




Besucherzähler-Counter.com