From ramasamy at cancer.org.uk  Fri Oct  1 15:17:25 2004
From: ramasamy at cancer.org.uk (Adaikalavan Ramasamy)
Date: Fri Oct  1 15:16:23 2004
Subject: [Rd] same test statistic for t-test with and without equal
	variance assumption
In-Reply-To: <1096635412.3412.10.camel@ndmpc126.ihs.ox.ac.uk>
References: <1096627733.3352.10.camel@ndmpc126.ihs.ox.ac.uk>
	<x2brfm666d.fsf@biostat.ku.dk>
	<1096635412.3412.10.camel@ndmpc126.ihs.ox.ac.uk>
Message-ID: <1096636645.3441.1.camel@ndmpc126.ihs.ox.ac.uk>

Apologies, I made an incorrect statement. The statistics from t-test
with difference variance assumptions are the same if both groups have
the same length. Sorry for troubling everyone again.


On Fri, 2004-10-01 at 13:56, Adaikalavan Ramasamy wrote:
> 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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[Rd] same test statistic for t-test with and without equal variance assumption
Adaikalavan Ramasamy