From: Adaikalavan Ramasamy <ramasamy_at_cancer.org.uk>

Date: Fri 01 Oct 2004 - 22:56:52 EST

R-devel@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-devel Received on Fri Oct 01 23:01:03 2004

Date: Fri 01 Oct 2004 - 22:56:52 EST

Peter, thank you! I forgot the to square root in calculating sp.

sp <- sqrt( ( (n1-1)*v1 + (n2-1)*v2 )/(n1 + n2 - 2) )

For several simulation runs, the test statistics from both tests are remarkably similar (difference is less than 10e-16). I naively assumed that the statistics value should be slightly but visibly different too.

It appear that the effects of equal and unequal variance assumptions are only felt through the degrees of freedom calculation.

Regards, Adai

On Fri, 2004-10-01 at 12:15, Peter Dalgaard wrote:

> Adaikalavan Ramasamy <ramasamy@cancer.org.uk> writes:

*>
**> > Could some kindly tell me if I am supposed to be getting the same test
**> > statistic value with var.equal=TRUE and var.equal=FALSE in t.test ?
**> >
**> > set.seed(1066)
**> > x1 <- rnorm(50)
**> > x2 <- rnorm(50)
**> >
**> > t.test(x1, x2, var.equal=FALSE)$statistic # 0.5989774
**> > t.test(x1, x2, var.equal=TRUE)$statistic # 0.5989774 ???
**> >
**> >
**> > Here are my own calculations that shows that perhaps the result when
**> > var.equal=TRUE is wrong.
**> >
**> > n1 <- length(x1); n2 <- length(x2)
**> > m1 <- mean(x1) ; m2 <- mean(x2) ; num <- (m1 - m2)
**> > v1 <- var(x1) ; v2 <- var(x2)
**> >
**> > # t-test with UNequal variance
**> > denom1 <- sqrt( v1/n1 + v2/n2 )
**> > num / denom1 # gives 0.5989774
**> >
**> > # t-test with equal variance
**> > sp <- ( (n1-1)*v1 + (n2-1)*v2 )/(n1 + n2 - 2)
**> > denom2 <- sp * sqrt( 1/n1 + 1/n2 )
**> > num / denom2 # gives 0.5913777
**> >
**> >
**> > I tested this using R-1.9.1 (21/06/2004) on Redhat Fedora Core 2 and
**> > Windows 2000 Professional with the same results.
**> >
**> > Any suggestions would be kindly appreciated.
**>
**> Your calculation is wrong. Try increasing the variance of x1 and x2...
**>
**> > set.seed(1066)
**> > x1 <- rnorm(50,,100)
**> > x2 <- rnorm(50,,100)
**> > m1 <- mean(x1) ; m2 <- mean(x2) ; num <- (m1 - m2)
**> > v1 <- var(x1) ; v2 <- var(x2)
**> > denom1 <- sqrt( v1/n1 + v2/n2 )
**> > num / denom1 # gives 0.5989774
**> [1] 0.5989774
**> > sp <- ( (n1-1)*v1 + (n2-1)*v2 )/(n1 + n2 - 2)
**> > denom2 <- sp * sqrt( 1/n1 + 1/n2 )
**> > num / denom2 # gives 0.5913777
**> [1] 0.005913777
**>
*

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https://stat.ethz.ch/mailman/listinfo/r-devel Received on Fri Oct 01 23:01:03 2004

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