Hi Nikolaos,
You might have sorted out your simulation from weibull, I just managed to write the codes given below: I thought it may help to thread it here in connection to your query for simulation from weibull and get further advices from others.
capture program drop wsim
program define wsim, rclass
version 9.2
syntax [, obs(integer 1) lambda(real 0.8) gamma(real 0.4) ]
drop _all
set obs `obs'
tempvar time event
gen `time' = ((log(1-uniform()))/-`lambda')^(1/`gamma')
summarize `time'
return scalar mean = r(mean)
end
simulate time=r(mean) , reps(1000): wsim, obs(100)
gen event= time< 5
HTH
Muhammad Riaz
--- On Mon, 3/2/09, Nikolaos Pandis <[email protected]> wrote:
From: Nikolaos Pandis <[email protected]>
Subject: Re: st: Weibull
To: [email protected]
Date: Monday, March 2, 2009, 9:48 PM
Dear Bobby,
Thank you very much for the posting.
I have the previous version of the book on survival analysis with Stata that you have coauthored with M. Cleves and W. Gould. Any sections in there that will help me with the current problem?
Best wishes,
Nikolaos
--- On Mon, 3/2/09, Roberto G. Gutierrez, StataCorp <[email protected]> wrote:
From: Roberto G. Gutierrez, StataCorp <[email protected]>
Subject: Re: st: Weibull
To: [email protected]
Date: Monday, March 2, 2009, 6:15 PM
Nikolaos Pandis <[email protected]> asks:
> I would like to generate continuous data for two groups for which I would
> like to evaluate whether there is a difference between their means (I could
> use use a t-test). I would like to be able to set the mean and sd of the two
> groups. The data would represent bond failure strength (in MPa) of two
> different materials (the 2 groups).
> Additionally, I would like to generate data for the same experiment that
> follows the Weibull distribution and compare the two groups.
> It is of interest to see the results of the analysis on the data under the
> ttest analysis and under an analysis suitable for the Weibull distribution.
> The objective is to show how different analyses of similar data might point
> to different results, and the importance of selecting the correct
> distribution and analysis.
Nikolaos has already received some very good advice, to which I would only add
that I have written the routine -gengammareg- available via
. findit gengammareg
-gengammareg- generates data from gamma regression as implemented by -streg-,
but also includes as special cases the exponential, Weibull and lognormal
distributions; see -help gengammareg- after installing.
The two-sample test Nikolaos describes can be retooled as regression on a
dummy variable, allowing the use of -gengammareg- here.
--Bobby
[email protected]
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