similar to: time varying covariates

Dear Prof. Brostr?m, Dear R-mailinglist, first of all thanks a lot for your great effort to incorporate time-varying covariates into aftreg. It works like a charm so far and I'll update you with detailled benchmarks as soon as I have them. I have one more questions regarding Accelerated Failure Time models (with aftreg): You mention that left truncation in combination with time-varying

Dear All, since years I am struggling with Surv objects in data.frames. The following seems to have to do with it. See below the modified example from the help page of survSplit. The original works, as expected. If, however, a Surv object is added to the data.frame, each record gets doubled. Is there some solution other than avoiding Surv objects in data.frames? Thanks, Heinz

Hello, coxph does not use any information that are in the dataset between event times (or "death times") , since computation only occurs at event times. For instance, removing observations when there is no event at that time in the whole dataset does not change the results: > set.seed(1) > data <- as.data.frame(cbind(start=c(1:5,1:5,1:4),stop=c(2:6,2:6,2:5),status=c(rep(

Dear R-users, I use the survsplit function in the survival package to change my data into counting-process format and the transformed format is as follow: (a) start stop event DP age .... 0 5 0 1 20 5 10 0 1 20 10 25 1 1 20 looking at the above three entries that belong to the same person, if an event happen at

Hi, I've seen in the NestCohort package that one can do a hazard model with a binary outcome using covariates. I am interested in multistate hazard models with time-varying covariates, but can't seem to find this already implemented in an R package. Is this included somewhere but called something else? I feel like I've looked all over. Thanks! Michaela Gulemetova-Swan

Hi! I want to estimate a shared gamma frailty model with left truncated data. I use a parametric baseline hazard so that I can use simple ML estimation. As I have a big data set it is ok to assume piecewise constant baseline hazards. As my data are left truncated I have modified the definition of the risk set. Do I also have to modifiy the frailty distribution if I have left truncated data?

Hi I'm trying to use the fold function as described here: http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-cox-regression.pdf Page9 It does say that you can use this when you have more than one time varying covariate: in the description of the argument cov it says: "cov: A vector giving the column numbers of the time-dependent covariate in data, or a list of vectors if there

Hi, 1. How do I construct 95% prediction interval for new x values, for example - x = 30000? 2. How do I construct 95% confidence interval? my dataframe is as follows : >dt structure(list(y = c(26100000, 60500000, 16200000, 30700000, 70100000, 57700000, 46700000, 8600000, 10000000, 61800000, 30200000, 52200000, 71900000, 55000000, 12700000 ), x = c(108000, 136000,

Am Montag, 2. Februar 2015, 17:44:53 schrieb Marc Muehlfeld: > Hello Andreas, > > Am 02.02.2015 um 13:00 schrieb Andreas Hauffe: > > I set up a new AD with the Sernet Samba 4.1 packages. I did the > > provisioning with "samba-tool domain provision --use-rfc2307 > > --interactive". I checked the dc, ldap, kerberos and dns services under > > linux.

Hi I have used a polycor package for categorical correlation coefficients. I run the following script. But there were no results. Could you tell me how to correct the script? Thanks in advance, vars <- names(sdi) for (i in 1:length(vars)) { for (j in 1:length(vars)) { paste(vars[i]," and ", vars[j]) polychor(vars[i], vars[j]) # corr } } -- Kum-Hoe Hwang, Ph.D.Phone :

Dear All, I'm analysing a negative binomial dataset from a population-based study. Many covariates were determined on household level, so all members of a household have the same value for those covariates. In STATA, there seems to be an option for 'clustered analysis' for neg-bin regression. Does an equivalent exist for R(MASS)'s glm.nb or a comparable function? Many thanks for

Another question about find. I looked at the gnome tool and tried to simulate what it is doing. I can't use it directly because it won't do sed. Basically I want to find all files with a string (except binary) and change it. let STR be the string I am looking for. NEW is new string. I am doing TFIL=/usr/tmp/dummy$$.txt find . -type f | while read fil do grep "$STR"

Hello, I set up a new AD with the Sernet Samba 4.1 packages. I did the provisioning with "samba-tool domain provision --use-rfc2307 --interactive". I checked the dc, ldap, kerberos and dns services under linux. Everything seems to work fine. Then I join a Windows 8.1 Enterprise running in as VM to the domain and login as administrator of the domain. When I install the RSAT and try

Hi, I have a linear mixed-effects model object and want to extract the 95% confidence intervals for the fixed and random effects, respectively. I found the function intervals() for confidence intervals for the fixed effects but no corresponding function for the random effects. Does it exist or do I have to calculate the confidence intervals for the random effects myself? Greetings, joerg

Hi, I would like to estimate something like y = a + b*d2*y + c*d3*y where the dummies are created from some vector d with three (actually many more) levels using factor(). But either there is included the variable y or d1*y. How could I get rid of these? Example: x = c(1,2,3,4,5,6,7,8) y = c(3,6,2,8,7,6,2,4) d = c(1,1,1,2,3,2,3,3) fd = factor(d) lm(x ~ fd*y) gives: Coefficients: (Intercept)

Dear all, I am new to R. I wish to use R's multiple imputation to deal with missing data. I have a data set with the size around 300 observations and 150 variables. I checked the help function in R and could not locate how to write the codes for this. can anyone give a hand? Do appreciate your time and kindness! Q. [[alternative HTML version deleted]]

Hi, I try to calculate Kendall's W coefficient and I have a bizarre error. little.app.mat<-matrix(c(1,3,4,2,6,5,2,4,3,1,5,6,3,2,5,1,5,4),nrow=3,byrow=TRUE) print(kendall.w(little.app.mat[-1,])) >>> Kendall's W for ordinal data >>> W = 0.7753623Error in if (is.na(x$p.table)) { : argument is of length zero

Dear R users, I am doing Cox regression using coxph(Survival) or cph(Design). I have time varying effects (diagnosed with schoenfeld residuals Chi2 test and graph) so I first want to split time into 2 separate intervals : t<6months and t>=6months, to estimate one hazard ratio (hr) for each interval. I am analysing Overall survival according to 3 prognostic factors (age,deep,ldh).

Hi. Please, how can I put together 2 or more lines at the same scatterplot ? Example: measures of protein intake (quantitative) of 4 children over 30 days, by day. How to plot all children at same graphic: Protein X Time ? Is there any command like "overlay" ? Thank you, Mauricio

Dear R list, I have an event history data set that is structured like this: Legislative act Discussion Agreement Time Event Act1 2006-05-30 2006-06-19 20 1 Act2 2004-03-01 2004-06-14 105 1 . . . I have information on the meetings in the legislature between adoption periods in a separate variable (the