gx.adjr2: Function to compute Adjusted r-squared values

Description Usage Arguments Note Author(s) See Also Examples

Description

Function to compute the Adjusted R-square value from the Multiple R-squared value displayed in the summary of a lm object. See Note below.

Usage

1
gx.adjr2(mr2, n, p)

Arguments

mr2

the Multiple R-squared value.

n

the number of cases in the regression model.

p

the number of independent (explanatory or predictor) variables in the model.

Note

The Adjusted R-squared value is a long established criterion. It may be calculated casually by this function, or may be extracted from a lm object, using summary(lm.object)[[9]]. However, users are urged to investigate Akaike's Information Criterion, AIC, as a procedure for comparing the fits of alternate models, and the use of the step function for automated model selection.

Author(s)

Robert G. Garrett

See Also

summary, AIC, step

Examples

1
2
gx.adjr2(0.7394, 111, 11)
gx.adjr2(0.713, 111, 6)

Example output

Loading required package: MASS
Loading required package: fastICA
  R^2 = 0.7394;  n = 111;  p = 11 	--  Adjusted R^2 = 0.713 

  R^2 = 0.713;  n = 111;  p = 6 	--  Adjusted R^2 = 0.699 

rgr documentation built on May 2, 2019, 6:09 a.m.

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