Hi when trying your code I got
pval = summary(model)$coeff[2,4] Error in summary(model)$coeff[2, 4] : subscript out of bounds > str(summary(model)$coeff) num [1, 1:4] 1.73e-17 7.07e-01 2.44e-17 1.00 - attr(*, "dimnames")=List of 2 ..$ : chr "(Intercept)" ..$ : chr [1:4] "Estimate" "Std. Error" "z value" "Pr(>|z|)" > You can see that this object is matrix with one row, so your subscript does not work and you has to define it correctly. How it is beyond my understanding of this topic. There are also warnings when estimating model, so maybe model is nod defined correctly > model = glm.nb(count~habitat,link="log") Warning messages: 1: In theta.ml(Y, mu, sum(w), w, limit = control$maxit, trace = control$trace > : iteration limit reached 2: In theta.ml(Y, mu, sum(w), w, limit = control$maxit, trace = control$trace > : iteration limit reached I did not check further. Regards Petr > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > project.org] On Behalf Of Kalia Schuster > Sent: Friday, October 03, 2014 4:19 AM > To: r-help@r-project.org > Subject: [R] (no subject) > > Hello, > I'm new to R. I'm trying to run a power analysis in a for loop to find > an ideal sample size. The situation is I am doing counts of fish at 24 > different sites and rating those sites as 1 or 2 for good or poor > habitat. > So the counts are continuous but the habitat rating isn't. When I try > to run a negative binomial general linearized model with given values > for mu: > exp1.302 and exp-0.32 and a given theta: exp(0.75), I get an error > message before I can run the whole loop and plot the power of the > sample size against sample. I used a template my teacher showed in > class, but since he used a poisson dist., I'm stuck on the glm.nb. > Please help! This is an assignment, so any suggestions would be > wonderful and I don't expect anything more. But please remember, I am a > beginner and only have a crude knowledge of R at this point. > Much appreciated. > > #Power analysis > rm(list=ls()) > graphics.off() > > set.seed(1) > alpha=0.05 > m=200 > > Ns = seq(2,40,2) > nNs = length(Ns) > NAs=rep(NA,nNs) > results= data.frame(n=Ns, power=NAs) > > for(j in 1:nNs) { > n=Ns[j] > reject_count = 0 > > for(i in 1:m ) { > > > mu_poor=exp(-0.32) > mu_suit=exp(1.302) > mu=c(rep(mu_poor,n/2),rep(mu_suit,n/2)) > theta=exp(0.175) > count=rnbinom(n=n,size=theta,mu=mu) > hab_poor=1 > hab_suit=2 > habitat=sample(hab_poor:hab_suit, size=n, replace=T) > model = glm.nb(count~habitat,link="log") > summary(model) > > > pval = summary(model)$coeff[2,4] > pval > reject = pval < alpha > if (reject) reject_count = reject_count+1 > } > reject_rate = reject_count/m > power = reject_rate > typeIIerror=1-reject_rate > > results[j,]$power=power > } > plot (x=Ns, y=results$power, xlab="Sample size", ylab="Power") > lines(Ns,rep(0.95,nNs)) > par(lty=2) > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code. ________________________________ Tento e-mail a jakékoliv k němu připojené dokumenty jsou důvěrné a jsou určeny pouze jeho adresátům. 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