Commonality Analysis
This function conducts commonality analyses based on an all-possible-subsets regression.
commonality(apsOut)
apsOut |
Output from /codeaps |
This function conducts commonality analyses based on an all-possible-subsets regression.
The function returns a matrix containing commonality coefficients and percentage of regression effect for each each possible set of predictors.
Kim Nimon <kim.nimon@gmail.com>
Nimon, K., Lewis, M., Kane, R. & Haynes, R. M. (2008) An R package to compute commonality coefficients in the multiple regression case: An introduction to the package and a practical example.Behavior Research Methods, 40, 457-466.
Nimon, K., & Oswald, F. L. (2013). Understanding the results of multiple linear regression: Beyond standardized regression coefficients. Organizational Research Methods, 16, 650-674.
## Predict paragraph comprehension based on three verbal
## tests: general info, sentence comprehension, & word
## classification
## Use HS dataset in MBESS
if (require ("MBESS")){
data(HS)
## All-possible-subsets regression
apsOut=aps(HS,"t6_paragraph_comprehension",
list("t5_general_information", "t7_sentence","t8_word_classification"))
## Commonality analysis
commonality(apsOut)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.