[R] Simple simulation in R

2003-08-26 Thread Peter Flom 
Hello all

I have a feeling this is very simple..but I am not sure how to do
it

My boss has two variables, one is an average of 4 numbers, the other is
an average of 3 of those numbers i.e

var1 = (X1 + X2 + X3 + X4)/4
var2 = (X1 + X2 + X3)/3

all of the X variables are supposed to be measuring similar constructs

not surprisingly, these are highly correlated (r = .98), the question
is how much of  this correlation is due to the fact that the X's are
related, and how much to the fact that the two VARs are similarly
constructed

What I want to do is simulate this with normally distributed data for
the X's.  That is, generate (say) 1000 sets of X1 through X4, use those
to caluculate 1000 var1 and var2, and then 1000 correlations between
var1 and var2, and then plot those results.

Any help appreciated

Peter Flom

Peter L. Flom, PhD
Assistant Director, Statistics and Data Analysis Core
Center for Drug Use and HIV Research
National Development and Research Institutes
71 W. 23rd St
www.peterflom.com
New York, NY 10010
(212) 845-4485 (voice)
(917) 438-0894 (fax)

__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help

Re: [R] Simple simulation in R

2003-08-26 Thread Thomas Petzoldt 
Hello all

I have a feeling this is very simple..but I am not sure how to do
it
My boss has two variables, one is an average of 4 numbers, the other is
an average of 3 of those numbers i.e
var1 = (X1 + X2 + X3 + X4)/4
var2 = (X1 + X2 + X3)/3
Hello Peter, try the following:


nsim  - 100
nsamp - 100
r - numeric(nsim)

for (i in 1:nsim) {
  dat - matrix(rnorm(4 * nsamp), ncol=4)
  v1 - rowSums(dat)/4
  v2 - rowSums(dat[,1:3])/3
  r[i] - cor(v1,v2)
}
plot(sort(r))

Hope it helps!

Thomas P.

__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help

RE: [R] Simple simulation in R

2003-08-26 Thread Liaw, Andy 
I believe simple math stat calculations should be sufficient for this.

For simplicity, assume X1 through X4 are iid with mean m and variance v.

Note that

  var1 = (3*var2 + x4) / 4

so
 
  cov(var1, var2) = cov(var2, (3*var2 + x4)/4)

and since var2 and x4 are independent, this covariance can be simplified.
Carry this through and substituting in m and v in the appropriate places
should give you the covariance (and hence correlation) in terms of m and
v.

Andy



 -Original Message-
 From: Peter Flom [mailto:[EMAIL PROTECTED] 
 Sent: Tuesday, August 26, 2003 10:31 AM
 To: [EMAIL PROTECTED]
 Subject: [R] Simple simulation in R
 
 
 Hello all
 
 I have a feeling this is very simple..but I am not sure 
 how to do it
 
 My boss has two variables, one is an average of 4 numbers, 
 the other is an average of 3 of those numbers i.e
 
 var1 = (X1 + X2 + X3 + X4)/4
 var2 = (X1 + X2 + X3)/3
 
 all of the X variables are supposed to be measuring similar constructs
 
 not surprisingly, these are highly correlated (r = .98), the 
 question is how much of  this correlation is due to the fact 
 that the X's are related, and how much to the fact that the 
 two VARs are similarly constructed
 
 What I want to do is simulate this with normally distributed 
 data for the X's.  That is, generate (say) 1000 sets of X1 
 through X4, use those to caluculate 1000 var1 and var2, and 
 then 1000 correlations between var1 and var2, and then plot 
 those results.
 
 Any help appreciated
 
 Peter Flom
 
 Peter L. Flom, PhD
 Assistant Director, Statistics and Data Analysis Core
 Center for Drug Use and HIV Research
 National Development and Research Institutes
 71 W. 23rd St
 www.peterflom.com
 New York, NY 10010
 (212) 845-4485 (voice)
 (917) 438-0894 (fax)
 
 __
 [EMAIL PROTECTED] mailing list 
 https://www.stat.math.ethz.ch/mailman/listinfo /r-help
 

--
Notice:  This e-mail message, together with any attachments,...{{dropped}}

__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help