Re: [R] find confounder in covariates

From: Spencer Graves <spencer.graves_at_pdf.com>
Date: Sat 23 Jul 2005 - 10:26:34 EST

          It was easier than I thought. To your example, just add one line:

 > alias(f)
Model :
y ~ z1 + z2 + z3

Complete :

      (Intercept) z1B z1C z3
z2Bb              1
z2Cc                  1

	  spencer graves

Young Cho wrote:

> Hi,
>
> I was wondering if there is a way, or function in R to
> find confounders. For istance,
>
>

>>a = sample( c(1:3), size=10,replace=T)
>>X1 = factor( c('A','B','C')[a] )
>>X2 = factor( c('Aa','Bb','Cc')[a] )
>>Xmat = data.frame(X1,X2,rnorm(10),rnorm(10))
>>dimnames(Xmat)[[2]] = c('z1','z2','z3','y')

>
>
> Now, z2 is just an alias of z1. There can be a
> collinearity like one is a linear combination of
> others. If you run lm on it:
>
>
>>f = lm(y~.,data=Xmat)
>>summary(f)

>
>
> Call:
> lm(formula = y ~ ., data = Xmat)
>
> Residuals:
> Min 1Q Median 3Q Max
> -1.2853 -0.3708 -0.1224 0.4617 1.2821
>
> Coefficients: (2 not defined because of singularities)
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 0.82141 0.44583 1.842 0.1150
> z1B -1.34167 0.65176 -2.059 0.0852 .
> z1C 0.80891 1.07639 0.751 0.4808
> z2Bb NA NA NA NA
> z2Cc NA NA NA NA
> z3 0.04231 0.23397 0.181 0.8625
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.'
> 0.1 ' ' 1
>
> Residual standard error: 0.971 on 6 degrees of freedom
> Multiple R-Squared: 0.5086, Adjusted R-squared:
> 0.2629
> F-statistic: 2.07 on 3 and 6 DF, p-value: 0.2057
>
> In this case, I can look at data and figure out which
> variable is confounded with which. But, if we have
> many categorial covariates ( not necessarily same
> number of levels ), it is almost impossible to check
> it out.
>
> Any help would be greatly appreicated. Thanks.
>
> Young.
>
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-- 
Spencer Graves, PhD
Senior Development Engineer
PDF Solutions, Inc.
333 West San Carlos Street Suite 700
San Jose, CA 95110, USA

spencer.graves@pdf.com
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Received on Sat Jul 23 10:33:54 2005

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