search for: bili

...weighted model, with the addition of a "weights=albumin" argument (I only chose albumin because it had no missing values, not because of any real relevance). Below are my code with the resulting error messages. Thanks in advance! > pfit <- coxph(Surv(time,status>0) ~ trt + log(bili) + log(protime) + age + + + platelet, data=pbc + ) > > pfit Call: coxph(formula = Surv(time, status > 0) ~ trt + log(bili) + log(protime) + age + +platelet, data = pbc) coef exp(coef) se(coef) z p trt -0.000624 0.999 0.17304 -0.003...

Hello, I wonder when I do coxph in R: coxph( Surv(start, stop, event) ~ x, data=test) If x is a categorical varible (1,2,3,4,5), should I creat four dummy varibles for it? if yes, how can I get the overall p value on x other than for each dummy variable? Thanks Lisa Wang Princess Margaret Hospital Phone 416 946 4501

Hi, I'm reading van Belle et al "Biostatistics" and trying to run a cox test using a dataset from: http://faculty.washington.edu/~heagerty/Books/Biostatistics/chapter16.html (Primary Biliary Cirrhosis data link at top of the page), I'm using the following code: --------------- start of code library(survival) liver <- scan("liver2.txt",list(age=0,albumin=0,alkphos=0,ascites=0,bili=0, cholest=0,edema=0,edmadj=0,hepmeg=0,obstime=0,platelet=0,protime=0,...

...model on the Mayo clinic's PBC data set (given in the "survival" package), the regression coefficients do not agree with the results presented in Table 4.6.3 (p. 195) of Fleming & Harrington's book. library(survival) data(pbc) ans.cox <- coxph(Surv(time, status) ~ log(bili) + log(alb) + age + log(protime) + edema) ans.cox > ans.cox <- coxph(Surv(time, status) ~ log(bili) + log(alb) + age + log(protime) + edema) > ans.cox Call: coxph(formula = Surv(time, status) ~ log(bili) + log(alb) + age + log(protime) + edema) coef exp(coef) se...

...oduce figure 4 of *Statistical Tables and Plots using S and LATEX* by Prof. Frank Harrell with the following code: rm(list=ls()) library(Hmisc) getHdata(pbc) attach(pbc) age.groups <- cut2(age, c(45,60)) g <- function(y) apply(y, 2, quantile, c(.25,.5,.75)) y <- with(pbc, cbind(Chol=chol,Bili=bili)) # You can give new column names that are not legal S names # by enclosing them in quotes, e.g. 'Chol (mg/dl)'=chol vars <- with(pbc, c(label(chol), label(bili))) label(y) <- paste(vars, collapse=' and ') # Will make nice caption in table s3 <- summary(y ~ age.groups...

...lt;- read.table(pbcurl, header=F, col.names=c('id', 'time', 'status', 'trt', 'age', 'sex', 'ascites', 'hepato', 'spiders', 'edema', 'bili', 'chol', 'albumin', 'copper', 'alk.phos', 'ast', 'trig', 'platelet', 'protime', 'stage'), na.strings='.') pbc$age <- pbc$age/...

...tors). When there is only 1 predictor in the model, termplot returns a "?". In this case, I have not been able to figure out how to create the desired plot. Otherwise,termplot is easy to use. Example: library(survival) library(splines) data(pbc) fit1<-coxph(Surv(time,status)~ns(bili,4)+ns(age,4), data=pbc) fit2<-coxph(Surv(time,status)~ns(bili,4), data=pbc) par(mfrow=c(2,2)) termplot(fit1) # returns two plots (one for bili and one for age) termplot(fit2) # returns a "?" prompt Does anyone have any suggestions for obtaining a plot of the log relative risk as a fu...

...attempting to use the ratetable argument to survexp in the survival package. I use the example from the ?survexp help page below, and then slightly modify it to produce an error. library(survival) data(pbc) #fit a model without any factors pfit1 <- coxph(Surv(time, status > 0) ~ trt + log(bili) + log(protime) + age + platelet, data=pbc) #this works as expected survexp(~ trt, ratetable = pfit1, data = pbc) #now I fit a similar model, simply adding the 'sex' term #note sex is now the only factor in the model pfit2 <- coxph(Surv(time, status > 0) ~ trt + log(bili...

...oing to get crazy with the pbc data set. I just want to apply simple cox regression in the data set. I am a beginner in R but I don't think I am doing anything wrong. I have the book of Fleming and Harrington 1990. I perform cox regression by typing: out<- coxph(Surv(times/365,status)~log(bili)+log(proth)+edema+log(albumin)+age) out Call: coxph(formula = Surv(times/365, status) ~ log(bili) + log(proth) +     edema + log(albumin) + age)                 coef exp(coef) se(coef)     z       p log(bili)     0.8636    2.3716  0.08294 10.41 0.0e+00 log(proth)    2.3868   10.8791  0.76851 ...

...0] <- 4 group[id>=200 & id<250] <- 5 group[id>=250 & id<300] <- 6 group[id>=300] <- 7 I estimate the following model, using the Pbc data (with time-varying covariates) from Therneau and Grambsch's book: fitf <- coxph(Surv(start,stop,event==2) ~ age + log(bili) + log(protime) + log(albumin) + edema + frailty(group), na.action=na.exclude, data=Pbcseq) Then I obtain: > fitf[10] $frail [1] 0.06273372 0.16192093 0.10050877 0.37716999 -0.20853156 -0.71887977 [7] -0.10922275 And: > fitf[11] $fvar...

This is a really rookie question: when should i use TE110P ISDN PRI Card? -- Necati DEM?R --------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.digium.com/pipermail/asterisk-users/attachments/20100621/07d2917f/attachment.htm

Hello, I am trying to find an R function to compute 'direct adjusted survival' with standard errors. A SAS-macro to do this is presented in Zhang X, Loberiza FR, Klein JP, Zhang MJ. A SAS macro for estimation of direct adjusted survival curves based on a stratified Cox regression model. Comput Methods Programs Biomed 2007;88:95-101. It appears that this method is not implemented in R.

...grid_4.5.0 nloptr_2.0.3 boot_1.3-30 lattice_0.22-6 > > # Create a data set of all PBC subjects with 4 or more values > count <- table(pbcseq$id) > data4 <- subset(pbcseq, id %in% names(count)[count>3]) > data4$year <- data4$day/365.25 > > fit <- lmer(log(bili) ~ year + (1+year | id), data4) -- more lines than I can capture -- = NULL, verbose = 0L, control = list(optimizer = "nloptwrap", restart_edge = TRUE, boundary.tol = 1e-05, calc.derivs = TRUE, use.last.params = FALSE, checkControl = list(check.nobs.vs.rankZ = "i...

...=times, method='constant', f=0)$y } describe.survival <- function(y) { km <- kmsurv(y, c(2,5)) c('2 Year'=km[1], '5 Year'=km[2], 'Mean, y'=sum(y[,1])/sum(y[,2])) } S <- with(pbc, Surv(fu.days/365.25, status)) s1 <- summary(S ~ age + albumin + ascites + bili + drug + edema + chol, fun=describe.survival, data=pbc) for(w in 1:2) { if(w==1) setpdf(f1a,sublines=1,h=5.25) else setpdf(f1b,sublines=1,h=5) plot(s1, which=if(w==1)1:2 else 3, cex.labels=.7, cex.group.labels=.7*1.15, subtitles=T, main='', pch=if(w==2) 16 else c('2','5'),...

...ma i u podzemnim prahistorijskim tunelima. Betz je autor vi?e knjiga, a njegova posljednja pod nazivom ?Krafte aus dem Nichts ? Geheimnisvolle Orte und ratselhafte Energien? tretira drevne megalitne lokacije, menhire, dolmene i sveti?ta. Prave?i komparativnu analizu zaklju?io je da su drevni narodi bili tehnolo?ki i nau?no mnogo napredniji nego ?to im to dozvoljava konvencionalna nauka. Nakon mjerenja u Visokom Betz je odr?ao predavanje za stru?ni tim Fondacije i volontere Pete smjene zaklju?uju?i da postoji prisustvo elektromagnetnog zra?enja na vrhu Bosanske piramide Sunca frekvencije 28.125 kHz...

# Dear list, # I am an R-beginner and # spent the last days looking for a method to insert tables produced # with R into a word document. I thought about SPPS: copy a table from # an SPO-file and paste it into a word document # (if needed do some formatting with that table). # Annother idea was, to produce a TEX-file, # insert it and make it a word-table. # I found the following libraries, which