Dear R-Help List,
I'm trying to simulate data from a conditional distribution, and  
haven't been able to modify my existing code to do so.  I searched  
the archives, but didn't find any previous post that matched my  
question.

n=10000
pop = data.frame(W1 = rbinom(n, 1, .2),
   W2 = runif(n, min = 3, max = 8), W3 = rnorm(n, mean=0, sd=2))
pop = transform(pop,
   A = rbinom(n, 1, .5))
pop = transform(pop,
   Y = rbinom(n, 1, 1/(1+exp(-(1.5*A-.05*W1-2*W2-2*W3+2*A*W1)))))

In this population the probability of being "diseased" (Y=1) is  
approx 0.030.  What I want to be able to do is specify a conditional  
distribution of (A, W1, W2, W3) given that Y=1 and one for (A, W1,  
W2, W3) given that Y=0.  Then I can sample diseased and non-diseased  
individuals from these distributions without having to simulate a  
large base population.  This will be particularly useful when the  
probability of being "diseased" is even smaller and I want a large  
number of diseased individuals.

Any pointers to do this would be extremely helpful!
Thank you,
Sherri Rose

UC Berkeley
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