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Hi R people, I have a very basic question to ask - I'm sorry if it's been asked before, but I searched the archives and could not find an answer. All the examples I found were much more complicated/nuanced versions of the problem - my question is much more simple. I have data with multiple, nested fixed effects (as I understand it, fixed effects are specified by the experimental design

Hi, I make a weibull survival regression using suvreg function. Bu when I try to get the P values from anova, it give me NAs: I'm using R 2.4.0 and survival 2.29 Look: m <- survreg(Surv(tempo,censor)~grupo*peso) anova(m) Df Deviance Resid. Df -2*LL P(>|Chi|) NULL NA NA 148 966.6416 NA grupo -2 25.6334407 146 941.0081 NA

Hi, I make a weibull survival regression using suvreg function. Bu when I try to get the P values from anova, it give me NAs: I'm using R version 2.4.0 Patched (2006-11-25 r39997) and survival 2.30 library Look: m <- survreg(Surv(tempo,censor)~grupo*peso) anova(m) Df Deviance Resid. Df -2*LL P(>|Chi|) NULL NA NA 148 966.6416 NA grupo

Hi, Parameters assessment in R with nls doesn't work, though it works fine with MS Excel with the internal solver :( I use nls in R to determine two parameters (a,b) from experimental data. m V C0 Ce Qe 1 0.0911 0.0021740 3987.581 27.11637 94.51206 2 0.0911 0.0021740 3987.581 27.41915 94.50484 3 0.0911 0.0021740 3987.581 27.89362

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934