From: Young Cho <iidn01_at_yahoo.com>

Date: Fri 22 Jul 2005 - 11:47:09 EST

Date: Fri 22 Jul 2005 - 11:47:09 EST

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')

> f = lm(y~.,data=Xmat)

> summary(f)

Call:

lm(formula = y ~ ., data = Xmat)

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. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.htmlReceived on Fri Jul 22 11:50:56 2005

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