On Fri, 17 Apr 2009, ONKELINX, Thierry wrote:
Dear all,
Could someone point me to a function or algorithm to generate random
bivariate binomial data?
Some details about what I'm trying to do. I have a dataset of trees who
were categorised as not damaged or damaged. Each tree is measured twice
(once in two consecutive years). The trees can recover from the damage
but the data is clearly correlated. As a (un)damaged tree is more likely
to stay (un)damaged. A GEE-model indicates a correlation of about 0.6
between the measures on the same tree.
The commonly used sampling models for such count data (see Bishop,
Fienberg, and Holland, Discrete Multivariate Analysis, 1975.) involve four
parameters. There are various parameterizations.
In your case, the total sample size (N), the proportion of
undamaged trees at the first (pr.undam.1), and the proportions at the
second time conditional on the first (p.undam.2.undam.1, p.undam.2.dam.1)
seems like reasonable way to parameterize the problem to do your
simulation.
If you have the marginal counts and the correlation, you can transform
them to the above parameterization by hacking through the algebra to find
the expected 2 by 2 table of counts as a function of the latter
parameters.
Then
y <- rbinom( N, 1, pr.undam.1 )
x <- rbinom( N, 1, ifelse(y==1, pr.undam.2.undam.1, pr.undam.2.dam.1 )
table(x,y)
should get you started
HTH,
Chuck
I need to simulate similar dataset to do some power calculations.
Best regards,
Thierry
------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
thierry.onkel...@inbo.be
www.inbo.be
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Charles C. Berry (858) 534-2098
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