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yhat (version 2.0-2)

commonality: Commonality Analysis

Description

This function conducts commonality analyses based on an all-possible-subsets regression.

Usage

commonality(apsOut)

Arguments

apsOut

Output from /codeaps

Value

The function returns a matrix containing commonality coefficients and percentage of regression effect for each each possible set of predictors.

Details

This function conducts commonality analyses based on an all-possible-subsets regression.

References

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.

See Also

aps calc.yhat dominance rlw

Examples

Run this code
# NOT RUN {
  ## Predict paragraph comprehension based on three verbal
  ## tests: general info, sentence comprehension, & word
  ## classification

  ## Use HS dataset in MBESS 
     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)
# }

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