[R] bonjour

Bonjour, je suis une étudiante en épidémiologie. j'utilise R pour mes analyses, et un souci dans le calcul de l'AIC,BIC, et je pense calcul la déviance puis à partir de là calculer ces informations manuellement mais j'ai trouvé quelque chose et je ne suis pas très si c'est la déviance que j'ai

Re: [R] bonjour

ais. Il y a peut-être une liste spécifique en > français, mais je ne la connais pas. > Ensuite, lis le "posting guide" (lien disponible à la fin de chaque email > posté sur la liste R). > > Si ces 2 étapes sont bien respectées, tu devrais obtenir des réponses. > > H

[R] svydesign syntax and deviance!

This message is for those familiar with the survey package. I need to do regression logistic and choose the best model which explain the impact of the indepndent variables by using AIC,BIC,... > sum.coef<-summary(svyglm(y~x1+x2+x3, design=design, family=quasibinomial(), data=data))$deviance is t

Re: [R] svydesign syntax and deviance!

it is correct to use the deviance from glm model for the svyglm. Regards. 2010/7/31 Thomas Lumley > On Sat, 31 Jul 2010, aline uwimana wrote: > > This message is for those familiar with the survey package. I need to do >> regression logistic and choose the best model which explain

Re: [R] model fit

AIC(sum.coef7) Erreur dans UseMethod("logLik") : pas de méthode applicable pour "logLik" I tried but no usemethod("loglik")-> svyglm doesn't use Likelihood. 2010/8/3 Brad Fulton > Hi Rwanuza > > > > Here is the code I used to calculate the BIC score from the AIC score > > > > Model.1=svyglm(a

[R] R: classification tree model!

# Classification Tree with rpart library(rpart) # grow tree fit <- rpart(y~ x1 + x2+ x3 + x4+ x5,method="class", data=data) printcp(fit) # display the results plotcp(fit) # visualize cross-validation results summary(fit) # detailed summary of splits # plot tree plot(fit, uniform=TRUE,main="Clas

Re: [R] Confidence Intervals for logistic regression

Dear Troy, use this commend, your will get IC95% and OR. logistic.model <- glm(formula =y~ x1+x2, family = binomial) summary(logistic.model) sum.coef<-summary(logistic.model)$coef est<-exp(sum.coef[,1]) upper.ci<-exp(sum.coef[,1]+1.96*sum.coef[,2]) lower.ci<-exp(sum.coef[,1]-1.96*sum.coef[,2])

[R] R:Backward elimination in svyglm function in R

Dear all, someone knows how to get the best fit model by using the svyglm function with backward elimination method. thanx [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PL

[R] R: Backward elimination in svyglm function in R

stepwise backward elimination in R is possible if we use the syvglm funtion in regression logistique? thanx -- Forwarded message -- From: aline uwimana Date: 2010/8/6 Subject: R:Backward elimination in svyglm function in R To: r-help@r-project.org Dear all, someone knows how

[R] Invitation à se connecter sur LinkedIn

LinkedIn Aline Uwimana requested to add you as a connection on LinkedIn: -- James, J'aimerais vous inviter à rejoindre mon réseau professionnel en ligne, sur le site LinkedIn. Aline Accept invitation from Aline Uwimana