yhat: commonalityCoefficients – R documentation

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commonalityCoefficients

Commonality Coefficents

Description

Commonality Coefficients returns a list of two tables. The first table CC contains the list of commonality coefficients and the percent variance for each effect. The second CCTotByVar totals the unique and common effects for each independent variable.

Usage

commonalityCoefficients(dataMatrix, dv, ivlist, imat=FALSE)

Arguments

`dataMatrix`	Dataset containing the dependent and independent variables
`dv`	The dependent variable named in the dataset
`ivlist`	List of independent variables named in the dataset
`imat`	Echo flag, default to FALSE

Details

When echo flag is true, transitional matrices during commonality coefficient calculation are sent to output window. Default for this option is false. When set to true, the intermediate matrices for each commonality coefficient and regression combinations are printed in the output window.

Value

`CC`	Matrix containing commonality coefficients and percentage of variance for each effect.
`CCTotalByVar`	Table of unique and common effects for each independent variable.

Author(s)

Kim Nimon <kim.nimon@gmail.com>

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.

Examples

## Predict miles per gallon based on vehicle weight, type of 
  ## carborator, & number of engine cylinders
     commonalityCoefficients(mtcars,"mpg",list("wt","carb","cyl"))

  ## Predict paragraph comprehension based on four verbal
  ## tests: general info, sentence comprehension, word
  ## classification, & word type 
  ## Use HS dataset in MBESS 
     if (require ("MBESS")){
     data(HS)
  ## Commonality Coefficient Analysis
     commonalityCoefficients(HS,"t6_paragraph_comprehension",list("t5_general_information",
       "t7_sentence","t8_word_classification","t9_word_meaning"))
     }

yhat

Interpreting Regression Effects

v2.0-3

GPL (>= 2)

Authors

Kim Nimon <kim.nimon@gmail.com>, Fred Oswald, and J. Kyle Roberts.

Initial release

2020-12-31