Thank you all R friends, I did think bout running a univariate logistic regression could work but in my case I guess the fisher.test() will work fine.
Best regards to all, Abraço forte e que a força esteja com você, Dr. Pedro Emmanuel A. A. do Brasil Instituto de Pesquisa Clínica Evandro Chagas Fundação Oswaldo Cruz Rio de Janeiro - Brasil 2010/3/6 <r-sig-epi-requ...@stat.math.ethz.ch> > Send R-sig-Epi mailing list submissions to > r-sig-epi@stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit > https://stat.ethz.ch/mailman/listinfo/r-sig-epi > or, via email, send a message with subject or body 'help' to > r-sig-epi-requ...@stat.math.ethz.ch > > You can reach the person managing the list at > r-sig-epi-ow...@stat.math.ethz.ch > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of R-sig-Epi digest..." > > > Today's Topics: > > 1. Re: epitools::oddsratio error numbers close to zero in cells? > (Philippe Glaziou) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Fri, 5 Mar 2010 13:53:48 +0100 > From: Philippe Glaziou <glaz...@gmail.com> > To: "r-sig-epi@stat.math.ethz.ch" <r-sig-epi@stat.math.ethz.ch> > Subject: Re: [R-sig-Epi] epitools::oddsratio error numbers close to > zero in cells? > Message-ID: > <3d3804221003050453s4931c07bk42ffe4bfc5b8b...@mail.gmail.com> > Content-Type: text/plain; charset=ISO-8859-1 > > On 5 March 2010 03:26, BXC (Bendix Carstensen) <b...@steno.dk> wrote: > > You can actually also get results from fisher.test when one of the > entries is 0. > > One of your confidence limits will just be either 0 or Inf. > > But that should hardly be a surprise. > > > > You could also try the twoby2 command from the Epi package which will > summarize your > > table analysis nicely. > > > >> m > > ? ? [,1] [,2] > > [1,] ?360 ? ?0 > > [2,] ? ?7 ?120 > >> fisher.test(m) > > > > ? ? ? ?Fisher's Exact Test for Count Data > > > > data: ?m > > p-value < 2.2e-16 > > alternative hypothesis: true odds ratio is not equal to 1 > > 95 percent confidence interval: > > ?1204.706 ? ? ?Inf > > sample estimates: > > odds ratio > > ? ? ? Inf > > > > Another approach is to run a logistic regression model. Using the same > data as above: > > > (dp <- data.frame (a=c(320,7,0,0), b=c(0,0,4,120), t=c(1,0,1,0))) > ? ?a ? b t > 1 320 ? 0 1 > 2 ? 7 ? 0 0 > 3 ? 0 ? 4 1 > 4 ? 0 120 0 > > > fit <- glm(cbind(a,b) ~ t, binomial, dp) > > The estimated odds ratio is here (OR=1371): > > > exp(coef(fit)) > (Intercept) ? ? ? ? ? t > ?5.833e-02 ? 1.371e+03 > > > And its confidence interval: > > > exp(confint(fit)) > Waiting for profiling to be done... > 2.5 % 97.5 % > (Intercept) 0.02466 0.1159 > t 442.87000 5551.2516 > > > With less unbalanced data, glm() gives results very close to those > from fisher.test() > > > dp2 > a b t > 1 320 0 1 > 2 200 0 0 > 3 0 100 1 > 4 0 150 0 > > > fit2 <- glm(cbind(a,b) ~ t, binomial, dp2) > > > exp(coef(fit2)) > (Intercept) t > 1.333 2.400 > > > exp(confint(fit2)) > Waiting for profiling to be done... > 2.5 % 97.5 % > (Intercept) 1.080 1.650 > t 1.766 3.274 > > > fisher.test(matrix(c(320,200,100,150),2)) > > Fisher's Exact Test for Count Data > > data: matrix(c(320, 200, 100, 150), 2) > p-value = 2.294e-08 > alternative hypothesis: true odds ratio is not equal to 1 > 95 percent confidence interval: > 1.742 3.309 > sample estimates: > odds ratio > 2.397 > > > > --Philippe > Senior Epidemiologist, > World Health Organization > Geneva, Switzerland > > > > ------------------------------ > > _______________________________________________ > R-sig-Epi mailing list > R-sig-Epi@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/r-sig-epi > > > End of R-sig-Epi Digest, Vol 40, Issue 2 > **************************************** > [[alternative HTML version deleted]]
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