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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