Hi all, In my continuous transition of GLIM to R I try to make a glm with binomial errors. The data file have 3 vectors: h -> the factor that is ajusted (have 3 levels) d -> number of animais alive (the response) n -> total number of animals To test proportion of alive, make d/n. In GLIM: $yvar d$ $error binomial n$ $fit +h$ scale deviance = 25.730 (change = -9.138) at cycle 4 d.f. = 15 (change = -2) factor h is significant by chisq? with 2df fron tables = 5.99 $disp e$ estimate se parameter 1 -0.1054 0.2055 1 2 0.7985 0.2961 h(2) 3 0.08827 0.26764 h(3) Scale parameter taken as 1.000 In R:> modelo.glex24.1 <- glm((d/n)~h,family=binomial)Warning message: non-integer #successes in a binomial glm! in: eval(expr, envir, enclos)> summary(modelo.glex24.1)Call: glm(formula = (d/n) ~ h, family = binomial) Deviance Residuals: Min 1Q Median 3Q Max -0.66227 -0.09918 -0.06041 0.18103 0.64740 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -0.06119 0.81688 -0.075 0.940 h2h 0.57994 1.17433 0.494 0.621 h3h 0.07761 1.15499 0.067 0.946 (Dispersion parameter for binomial family taken to be 1) Null deviance: 2.0737 on 17 degrees of freedom Residual deviance: 1.7843 on 15 degrees of freedom AIC: 31.147 Number of Fisher Scoring iterations: 2> anova.glm(modelo.glex24.1,test="Chisq")Analysis of Deviance Table Model: binomial, link: logit Response: (d/n) Terms added sequentially (first to last) Df Deviance Resid. Df Resid. Dev P(>|Chi|) NULL 17 2.07368 h 2 0.28935 15 1.78433 0.86530>The values calculate by GLIM and R is very different, in GLIM h is significant and in R no. What is my error???? Another question is: I make a barplot graphic with mean of (d/n) by h and I need to plot a SE bar. The SE used is the same value returned by summary or need to make transformations like means (1/(1+1/odds ratio))? Thanks for all Ronaldo -- Newman's Discovery: Your best dreams may not come true; fortunately, neither will your worst dreams. -- | //|\\ [*****************************][*******************] || ( ? ? ) [Ronaldo Reis J?nior ][PentiumIII-600 ] | V [ESALQ/USP-Entomologia, CP-09 ][HD: 30 + 10 Gb ] || / l \ [13418-900 Piracicaba - SP ][RAM: 128 Mb ] | /(lin)\ [Fone: 19-429-4199 r.229 ][Video: SiS620-8Mb ] ||/(linux)\ [chrysopa at insecta.ufv.br ][Modem: Pctel-onboar] |/ (linux) \[ICQ#: 5692561 ][SO: CL 7.0 (2.2.19)] || ( x ) [*****************************][*******************] ||| _/ \_Powered by Conectiva Linux 7.0 D+:) | Lxuser#: 205366 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
On Fri, 1 Mar 2002, Ronaldo Reis Jr. wrote:> In my continuous transition of GLIM to R I try to make a glm with binomial > errors. > > The data file have 3 vectors: > h -> the factor that is ajusted (have 3 levels) > d -> number of animais alive (the response) > n -> total number of animals > > To test proportion of alive, make d/n. > > In GLIM: > > $yvar d$ > > $error binomial n$ > > $fit +h$ > > scale deviance = 25.730 (change = -9.138) at cycle 4 > d.f. = 15 (change = -2) > > factor h is significant by chisq² with 2df fron tables = 5.99 > > $disp e$ > > estimate se parameter > 1 -0.1054 0.2055 1 > 2 0.7985 0.2961 h(2) > 3 0.08827 0.26764 h(3) > Scale parameter taken as 1.000 > > In R: > > > modelo.glex24.1 <- glm((d/n)~h,family=binomial) > Warning message: > non-integer #successes in a binomial glm! in: eval(expr, envir, enclos)Please don't ignore warnings.> > summary(modelo.glex24.1) > > Call: > glm(formula = (d/n) ~ h, family = binomial) > > Deviance Residuals: > Min 1Q Median 3Q Max > -0.66227 -0.09918 -0.06041 0.18103 0.64740 > > Coefficients: > Estimate Std. Error z value Pr(>|z|) > (Intercept) -0.06119 0.81688 -0.075 0.940 > h2h 0.57994 1.17433 0.494 0.621 > h3h 0.07761 1.15499 0.067 0.946 > > (Dispersion parameter for binomial family taken to be 1) > > Null deviance: 2.0737 on 17 degrees of freedom > Residual deviance: 1.7843 on 15 degrees of freedom > AIC: 31.147 > > Number of Fisher Scoring iterations: 2 > > > anova.glm(modelo.glex24.1,test="Chisq") > Analysis of Deviance Table > > Model: binomial, link: logit > > Response: (d/n) > > Terms added sequentially (first to last) > > > Df Deviance Resid. Df Resid. Dev P(>|Chi|) > NULL 17 2.07368 > h 2 0.28935 15 1.78433 0.86530 > > > > The values calculate by GLIM and R is very different, in GLIM h is > significant and in R no. > > What is my error????You forgot the weights, the analogue of `binomial n'. You want either glm(cbind(d, n-d) ~ h, family = binomial) or glm(d/n ~ h, weights = n, family = binomial) This is discussed in lots of places in the R literature, too many for me to point you to them all, but Venables & Ripley springs to mind .... -- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._