[R] slightly extended lm class

From: ivo welch <ivowel_at_gmail.com>
Date: Tue 02 Jan 2007 - 02:00:50 GMT


Dear R readers:

I have written a short lme.R function, which adds normalized coefficients and White heteroskedasticity-adjusted statistics to the standard output. Otherwise, it behaves like lm. This is of course trivial for experts, but for me and other amateur users perhaps helpful.

  y= rnorm(15); x= rnorm(15); z= rnorm(15);   m= lme( y ~ x + z); print(summary(m));

produces something like

Call:
lm(formula = ..1)

Residuals:

   Min 1Q Median 3Q Max
-26.04 -10.61 1.55 13.84 28.84

Coefficients:

            Estimate NormEst Std. Error t value Pr(>|t|) t-htsk Pr(>|th|)
(Intercept)   6.1343  0.0000     5.8886  1.0417   0.3181   1.41     0.183
x             0.6981  0.1109     1.5922  0.4385   0.6688   0.37     0.716
z            -0.7720 -0.4735     0.4123 -1.8727   0.0857  -2.06     0.062 .

---

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 18.7 on 12 degrees of freedom Multiple R-Squared: 0.233, Adjusted R-squared: 0.106 F-statistic: 1.83 on 2 and 12 DF, p-value: 0.203

If anyone is interested, it is available at "http://welch.econ.brown.edu/computers/lme.R". I didn't even get the formatting on the coefficient matrix right, but this is cosmetic. maybe other errors in it, too. of course, it would be nice if someone made something industrial strength out of this---for use by casual amateurs such as myself.

hope it helps someone.

regards,

/iaw



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