similar to: difference between coxph and cph

Hello. I get a bit confused by the output from the predict function when used on an object from coxph in combination with p-spline, e.g. fit <- coxph(Surv(time1, time2, status)~pspline(x), Data) predict(fit, newdata=data.frame(x=1:2)) It seems like the output is somewhat independent of the x-values to predict at. For example x=1:2 gives the same result as x=21:22. Does the result span the

hello: my data looks like: time1  time2   event  catagoria 2004    2006        1            C 2004    2005        0            C 2005    2010        1            E 2007    2009        1            C 2006    2007        0            E 2008    2010        0            C 2008    2010        1            E ... and the census interval is 1 year I have tried  this

The coxph function in R is not working for me when I use a continuous predictor in the model. Specifically, it fails to converge, even when bumping up the number of max iterations or setting reasonable initial values. The estimated Hazard ratio from the model is incorrect (verified by an AFT model). I've isolated it to the "x1" variable in the example below, which is log-normally

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

Hi r users, I have two data sets (X1, X2). For example, time1<-c( 0, 8, 15, 22, 43, 64, 85, 106, 127, 148, 169, 190 ,211 ) outpue1<-c(171 ,164 ,150 ,141 ,109 , 73 , 47 ,26 ,15 ,12 ,6 ,2 ,1 ) X1<-cbind(time1,outpue1) time2<-c( 0 ,8 ,15 , 22 ,43 , 64 ,85 ,106 ,148) output2<-c( 5 ,5 ,4 ,5 ,5 ,4 ,1 ,2 , 1 ) X2<-cbind(time2,output2) I want to

Hi, I would like to merge two data frames. It is just that I want the merging to be done with some kind of a fuzzy criterion. Let me explain. My first data frame looks like this : ID1 time1 dt 1 2008-01-02 13:11 10 2 2008-01-02 14:20 20 3

Full_Name: Suharto Anggono Version: 2.8.1 OS: Windows Submission from: (NULL) (125.165.84.118) PR#14076 inspired me to write this. > t1 <- as.POSIXct("1970-01-01 00:00:00", tz="GMT") > t2 <- as.POSIXlt("1970-01-01 00:00:00", tz="GMT") > t1 - t2 Time difference of 7 hours Above, t1 and t2 represent the same time in the same specified

Hello all, I've 2 strings that representing the start and end values of a date and time. For example, time1 <- c("21/04/2005","23/05/2005","11/04/2005") time2 <- c("15/07/2009", "03/06/2008", "15/10/2005") as.difftime(time1,time2) Time differences in secs [1] NA NA NA attr(,"tzone") [1] "" How can i

To Whomever is Interested, I have spent several days searching the web, help files, the R wiki and the archives of this mailing list for a solution to this problem, but nonetheless I apologize in advance if I have missed something obvious. The problem is this; I have a 5-column data frame with about 4.2 million rows, and want to create a new (and hopefully much smaller) data frame that

Further pursuing my curiosity to measure the efficiency of R/C++ interface, I conducted a simple matrix-vector multiplication test using .C and .Call functions in R. In each case, I measured the execution time in R, as well as inside the C++ function. Subtracting the two, I came up with a measure of overhead associated with each call. I assume that this overhead would be non-existent of the entire

Hello, Below is the code for a basic bar graph. I was seeking advice regarding the following: (a) For each time period there are values from 16 people. How I can change the colour value so that each person has a different colour, which recurs across each of the three graphs/tie epriods? (b) I have seen much more sophisticated examples using lattice (e.g each person has a separate

I am trying to build a model to aid a clinical decision. Certain patients have a blood marker measured at each visit - a rise of this may indicate recurrence of the cancer after treatment (endpoint is "clinical recurrence", censored). In a proportion (up to 30%), this rise is a false positive - hence I wish to correlate factors at the time of the rising test to clinical recurrence,

Dear R users, My apologies for the simple question, as I'm starting to learn the concepts behind the Cox PH model. I was just experimenting with the survival and rms packages for this. I'm simply trying to obtain the expected survival time (as opposed to the probability of survival at a given time t). I can't seem to find an option from the "type" argument in the predict

Hi all I am running a 2-way repeated measure anova with 1 between-subjects factor (Group=treatment, control), and 1 within-subject factor (Time of measurement: time1, time2). I extract the results of the anova with: summary(aov(effect ~ Group*Time + Error=Subj/Time, data=mydata)) Now, this must be clearly a dumb question, but how can I quickly extract in R all the post-hoc t-tests for the

Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c((0*INTERVAL):(6*INTERVAL))) TIME2

Dear all, I would like to have all unique combinations in the following matrix TimeIndex<- rbind (c(1,"Week_of_21_07-29_03"),           c(2,"Thursday_21_03"),           c(3,"Friday_22_03"),           c(4,"Saturday_23_03"),           c(5,"Sunday_24_03"),           c(6,"Monday_25_03"),           c(7,"Tuesday_26_03"),        

I'm trying to fit a Cox proportional hazards model to some hospital admission data. About 25% of the patients have had at least one admission, and of these, 40% have had two admissions within the 12 month period of the study. Each patients has had one of 4 treatments, and one of the treatment groups has had no admissions for the period. I used:

time1 = 2008-03-09 time2 = 2010-9-10 How to compute how many years between time1 and time2? Thanks! best [[alternative HTML version deleted]]

For a model I am working on, I have samples organized by year and week of the year. For this model, the data (year and week) comes from the basic sample data, but I require a value representing the amount of time since the sample was taken (actually, for the purpose of the model, it is sufficient to use the number of weeks from the middle of the sample week to the present). What I have found so

Dear All, what determines if a difference between POSIXct objects gets expressed in days or seconds? In the following example, it's sometimes seconds, sometimes days. as.POSIXct('2009-09-01') - as.POSIXct(NA) Time difference of NA secs c(as.POSIXct('2009-09-01'), as.POSIXct(NA)) - c(as.POSIXct('2009-09-01'), as.POSIXct('2009-08-31')) Time differences in