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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Stata and R |

Date |
Thu, 27 Aug 2009 11:47:43 -0500 |

What happens to ProbCE object that you create here? That might be what you tried to rbind, rather than INB in your last line of the cycle. I would assume this is what you want to do. As always, there are multiple ways of getting what you need there. You were given a Mata solution, which looks an overkill to me, and hardly is directly usable in further analysis. If you want a Stata variable as a result, there are two ways of going there. 1. A somewhat clumsy way of trying to have everyting in the same data set: assume that you have -eff- and -cost- variables for each observation. Then you could do this: capture noisily set obs 1000 * might give you an error message if you already have more than 1000 observations; * we might want to capture that error message gen INBsign = . gen ceas = . * this is what we will fill in gen n = _n in 1/1000 * _n is the notation for the current observation number * the range restriction limits the values to be from 1 to 1000 forvalues n=1/1000 { * n is what is known as a local macro in Stata jargon; * has a special reference format with opening and closing quotes replace INBsign = (eff*`n' - cost>0) sum INBsign, meanonly replace ceas = r(mean) in `n' * uses the return value from -summarize- command * replaces a single value in `n'-th line of data } 2. What I think is a more elegant solution is to create a separate Stata data set. In your R code, you create a separate ceas object; unfortunately Stata can only think of one data set in memory: postfile topost n probce using ceas, replace * declares a new file ceas.dta to be created that is to contain two variables, n and probce count if ~missing(eff) local denom = r(N) * again, it is using the return value of the previous command forvalues n=1/1000 { count if eff*`n'-cost > 0 post topost (`n') ( r(N)/`denom' ) * writes a new line to the ceas data set } postclose topost use ceas, clear HTH, Stas On Thu, Aug 27, 2009 at 12:44 AM, Frank Peter<frankpeter@safe-mail.net> wrote: > Dear All, > > This is to thank everybody for all their answers, I have really learn a lot from the answers. > > I was trying to generate cost-effectiveness acceptability curve. The R codes I was referring to were: > ======================================== > ceac = c() > denom = length(effectiveness) > for (n in 1000) { > INB = effectiveness*n - cost > ProbCE = length(subset(INB, INB>=0))/denom > ceac = rbind(ceac, c(n, INB)) > } > ======================================== > > Thanks > > Frank > reference: > Fenwick E, Marshall DA, Levy AR, Nichol G. Using and interpreting cost-effectiveness acceptability curves: an example using data from a trial of management strategies for atrial fibrillation. BMC Health Serv Res. 2006 Apr 19;6:52. (http://www.biomedcentral.com/1472-6963/6/52) > -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: Stata and R***From:*"Frank Peter" <frankpeter@Safe-mail.net>

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