Re: [R] making a plot

ex=1.5,adj=0.5) > > > > > > > Draw your plot, then write the code, locate the cursor on your plot, put > > the symbols where you want itl and click. > > > > Regards, > > > > > > Andrés > > > > PS ?locator > > > > > &g

[R] making a plot

Dear all, I am struggling to make a plot for my survival analysis class. This is my script labels<-c('1','2','3','4','5','6') ano<-c(2001,2002,2003,2004,2006,2008) ranges<-c(6,3,4,5,4,2) dotchart(ano, labels=labels, xlab='ano', ylab='Pacientes',pch=20,xlim=c(min(ano), max(ano+ranges))) se

Re: [R] Kaplan Meier analysis: 95% CI wider in R than in SAS

val probability is 0. > at > a certain time. The log-log transformation blows up. > Frank > > Enrico Colosimo wrote > > > > What are the significant problems of the log-log transformations? > > Any papers published about it? > > Enrico. > > > > > &

Re: [R] Kaplan Meier analysis: 95% CI wider in R than in SAS

What are the significant problems of the log-log transformations? Any papers published about it? Enrico. 2012/4/14 Frank Harrell > I used log-log in my book too until Terry Therneau alerted me to the > significant problems this creates. In the 2nd edition it will use log > S(t). > Frank > > Pa

[R] lme command

Hi, I am doing a longitudinal data set fit using lme. I used two forms of the lme command and I am getting two different outputs. FIRST out<-lme(Altura~Idade+Idade2+sexo+status+Idade:sexo+Idade:status+Idade2:sexo+Idade2:status, random=(list(ident=~Idade+Idade2))) SECOND out<-lme(Altura~Idade+Ida

[R] glm output for binomial family

ry(ajust2) # Coefficients: (Intercept)            x     1.3107      -0.2017 Degrees of Freedom: 2 Total (i.e. Null);  1 Residual Null Deviance:      3.958 Residual Deviance: 3.718        AIC: 9.104 = It seems that there is problem with the f