similar to: predicted HR in coxph with psline

Displaying 20 results from an estimated 900 matches similar to: "predicted HR in coxph with psline"

2011 Apr 06
1
help on pspline in coxph
Hi there, I have a question on how to extract the linear term in the penalized spline in coxph. Here is a sample code: n=100 set.seed(1) x=runif(100) f1 = cos(2*pi*x) hazard = exp(f1) T = 0 for (i in 1:100) { T[i] = rexp(1,hazard[i]) } C = runif(n)*4 cen = T<=C y = T*(cen) + C*(1-cen) data.tr=cbind(y,cen,x) fit=coxph(Surv(data.tr[,1],
2008 Apr 23
2
help on coxph.wtest
Hi, i need to use pspline. In this pspline function coxph.wtest was used. When I try to make some change to this function by pulling out the pspline function, it turns out R gave me an error msg, saying coxph.wtest cannot be found. Even if i dont change anything in pspline and just rename it and run the function, it did not work out. Can any one help me with this? is there anyway to get the
2008 May 09
1
predicting from coxph with pspline
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
2003 Apr 01
2
predict in Pspline package (PR#2714)
To whom it may concern, I don't know whether this is really a bug with the Pspline package or only a problem with my installation. Things work fine in Linux but not in Mac OS X (Darwin). Both system run the latest public versions of R and Pspline. predict.smooth.Pspline produces only NaN instead of predicted values when norder>2: > library (Pspline) > tt <- seq
2013 Feb 28
2
predict.smooth.Pspline function not found
I have a simple question that irritatingly I haven't been able to figure out on my own. It seems that some functions from the "Pspline" package are successfully installed while others are not. The code with which I'm working is more complicated, but the following highlights my problem. If I run the following code > tt <- seq (0,1,length=20) > xt <- tt^3 > fit
2003 Jan 22
1
something wrong when using pspline in clogit?
Dear R users: I am not entirely convinced that clogit gives me the correct result when I use pspline() and maybe you could help correct me here. When I add a constant to my covariate I expect only the intercept to change, but not the coefficients. This is true (in clogit) when I assume a linear in the logit model, but the same does not happen when I use pspline(). If I did something similar
2017 Nov 01
3
Cox Regression : Spline Coefficient Interpretation?
Hi, I'm using a Cox-Regression to estimate hazard rates on prepayments. I'm using the "pspline" function to face non-linearity, but I have no clue how to interpret the result. Unfortunately I did not find enough information on the "pspline" function wether in the survival package nor using google.. I got following output: * library(survival)* > > > >
2002 Nov 25
2
Pspline smoothing
Dear all, I'm trying to use the Pspline add-on package to fit a quintic spline (norder =3), but I keep running into a Singularity error. > traj.spl <- smooth.Pspline(time, x, norder=3 ) Error in smooth.Pspline(time, x, norder = 3) : Singularity error in solving equations > Playing around with the other parameters produces an "unused arguments" error: > traj.spl
2010 Nov 29
1
Evaluation of survival analysis
Dear all, May I ask is there any functions in R to evaluate the fitness of "coxph" and "survreg" in survival analysis, please? For example, the results from Cox regression and Parametric survival analysis are shown below. Which method is prefered and how to see that / how to compare the methods? 1. coxph(formula = y ~ pspline(x1, df = 2))
2024 Dec 16
1
Changes in the survival package (long)
The latest version of the survival package has two important additions. In prior code the call coxph(Surv(time, status) ~ age + strata(inst), data=lung) could fail if a version of either Surv() or strata() existed elsewhere on the search path; the wrong function could be picked up. Second, a model with survival::strata(inst) in the formula would not do what users expect. These
2008 Nov 25
1
how to check linearity in Cox regression
On examining non-linearity of Cox coefficients with penalized splines - I have not been able to dig up a completely clear description of the test performed in R or S-plus. >From the Therneau and Grambsch book (2000 - page 126) I gather that the test reported for "linear" has as its null hypothesis that the spline coefficient is the same at the center of basis. Thus, in the example
2011 May 29
1
Fitting spline using Pspline
Hey all, I seem to be having trouble fitting a spline to a large set of data using PSpline. It seems to work fine for a data set of size n=4476, but not for anything larger (say, n=4477). For example: THIS WORKS: ----------------------------- random = array(0,c(4476,2)) random[,1] = runif(4476,0,1) random[,2] = runif(4476,0,1) random = random[order(random[,1]),] plot(random[,1],random[,2])
2010 Nov 17
1
where are my pspline knots?
Hi All, I am trying to figure out how to get the position of the knots in a pspline used in a cox model. my.model = coxph(Surv(agein, ageout, status) ~ pspline(x), mydata) # x being continuous How do I find out where the knot of the spline are? I would like to know to figure out how many cases are there between each knot. Best, Federico -- Federico C. F. Calboli Department of Epidemiology
2001 Sep 10
1
data format for ppinit
After installation of R into VineLinux2.1.5, I started to enjoy statistics following some instruction, and found it very useful. One of my main purpose to use R is to try spatial statistics. Since library named "spatial" has already installed, I just tried ... > library(spatial) > towns <- ppinit(test.dat) ------- test.dat ------- x,y 4,7 5,7 5,8 5,9 6,7 6,8 6,9 7,8
2006 May 16
1
survival package - pspline
help Hello, I?m a statistic student in Austria and I have to do a survival analysis in R by using psplines as regressor. My problem is that I sometimes (I think it depends on the choose of the parameters) get a error message, but I do not know what it means. After that I tried the procedure with an example dataset R is providing. Although using the cancer dataset I also get this message. Input:
2010 Jul 09
4
Mysterious behavior
I had trouble with some tests for the survival suite last night that I cannot explain. Framework: Ubuntu Linux, R2.11. For testing survival I have a separate directory and Makefile. I pull everything into the local .RData, no packages, library, or namespace. (It's easier to add test modifications to a routine in a chain of calls). A test of survreg + psline would fail because
2002 Jan 04
1
RH and packages
Dear colleagues, I just upgraded to 1.4.0 version from RH RPM on a RH72 linux i686 machine. Maybe I am the only one, but when I tried then to install 2 packages (namely pspline and xgobi), weird things happened. First on call of library(xgobi) or library(help=xgobi), all looks good, but on call of ?xgobi, or data(PaulKAI), or when trying to look at html help, the package seems empty. More
2012 Jul 26
0
Using pspline in bic.surv of BMA package
Hi, I'm trying to using pspline in bic.surv{BMA}. ############################# library(BMA) library(survival) data(veteran) test.bic.surv<- bic.surv(Surv(time,status) ~ karno+pspline(age,df=3)+diagtime+prior, data = veteran, factor.type = TRUE) summary(test.bic.surv, conditional=FALSE, digits=2) ############################# The results are:
2009 Apr 26
1
how to install R really *locally*?
Hello, my first attempt at installing version 2.9.0 failed because I got an error "Error in library(pspline) : there is no package called 'pspline'" Later I realised that this comes from HOME/.RProfil, and removing that files "solves" that problem. However, I'm actually glad that this error happened, since it shows a deeper problem (which is actually not solved
2010 Dec 07
0
coxph failure
Larry, You found a data set that kills coxph. I'll have to think about what to do since on the one hand it's your own fault for trying to fit a very bad model, and on the other I'd like the routine to give a nice error message before it dies. In the data set you sent me the predictor variable is very skewed: > quantile(anomaly1$CREAT, c(0, .5, .9, .999, 1)) 0% 50%