mistake in multivePenal but not in frailtyPenal

Question

The libraries used are: library(survival) library(splines) library(boot) library(frailtypack) and the function used is in the library frailty pack.
In my data I have two recurrent events(delta.stable and delta.unstable) and one terminal event (delta.censor). There are some time-varying explanatory variables, like unemployment rate(u.rate) (is quarterly) that's why my dataset has been splitted by quarters. Here there is a link to the subsample used in the code just below, just in case it may be helpful to see the mistake. https://www.dropbox.com/s/spfywobydr94bml/cr_05_males_services.rda The problem is that it takes a lot of time running until the warning message appear.

Main variables of the Survival function are: I have two recurrent events: delta.unstable (unst.): takes value one when the individual find an unstable job. delta.stable (stable): takes value one when the individual find a stable job. And one terminal event delta.censor (d.censor): takes value one when the individual has death, retired or emigrated.

row     id contadorbis unst. stable d.censor    .t0 .t
1   78  1   0   1   0   0   88
2   101 2   0   1   0   0   46
3   155 3   0   1   0   0   27
4   170 4   0   0   0   0   61
5   170 4   1   0   0   61  86
6   213 5   0   0   0   0   92
7   213 5   0   0   0   92  182
8   213 5   0   0   0   182 273
9   213 5   0   0   0   273 365
10  213 5   1   0   0   365 394
11  334 6   0   1   0   0   6
12  334 7   1   0   0   0   38
13  369 8   0   0   0   0   27
14  369 8   0   0   0   27  119
15  369 8   0   0   0   119 209
16  369 8   0   0   0   209 300
17  369 8   0   0   0   300 392

When I apply multivePenal I obtain the following message:

Error en aggregate.data.frame(as.data.frame(x), ...) : 
arguments must have same length
Además: Mensajes de aviso perdidos

In Surv(.t0, .t, delta.stable) : Stop time must be > start time, NA created
#### multivePenal function
fit.joint.05_malesP<multivePenal(Surv(.t0,.t,delta.stable)~cluster(contadorbis)+terminal(as.factor(delta.censor))+event2(delta.unstable),formula.terminalEvent=~1, formula2=~as.factor(h.skill),data=cr_05_males_serv,Frailty=TRUE,recurrentAG=TRUE,cross.validation=F,n.knots=c(7,7,7), kappa=c(1,1,1), maxit=1000, hazard="Splines")

I have checked if Surv(.t0,.t,delta.stable) contains NA, and there are no NA's.

In addition, when I apply for the same data the function frailtyPenal for both possible combinations, the function run well and I get results. I take one week looking at this and I do not find the key. I would appreciate some of light to this problem.

#delta unstable+death

enter code here

fit.joint.05_males<-frailtyPenal(Surv(.t0,.t,delta.unstable)~cluster(id)+u.rate+as.factor(h.skill)+as.factor(m.skill)+as.factor(non.manual)+as.factor(municipio)+as.factor(spanish.speakers)+ as.factor(no.spanish.speaker)+as.factor(Aged.16.19)+as.factor(Aged.20.24)+as.factor(Aged.25.29)+as.factor(Aged.30.34)+as.factor(Aged.35.39)+ as.factor(Aged.40.44)+as.factor(Aged.45.51)+as.factor(older61)+ as.factor(responsabilities)+
terminal(delta.censor),formula.terminalEvent=~u.rate+as.factor(h.skill)+as.factor(m.skill)+as.factor(municipio)+as.factor(spanish.speakers)+as.factor(no.spanish.speaker)+as.factor(Aged.16.19)+as.factor(Aged.20.24)+as.factor(Aged.25.29)+as.factor(Aged.30.34)+as.factor(Aged.35.39)+as.factor(Aged.40.44)+as.factor(Aged.45.51)+as.factor(older61)+ as.factor(responsabilities),data=cr_05_males_services,n.knots=12,kappa1=1000,kappa2=1000,maxit=1000, Frailty=TRUE,joint=TRUE, recurrentAG=TRUE)

###Be patient. The program is computing ... 
###The program took 2259.42 seconds 

#delta stable+death
fit.joint.05_males<frailtyPenal(Surv(.t0,.t,delta.stable)~cluster(id)+u.rate+as.factor(h.skill)+as.factor(m.skill)+as.factor(non.manual)+as.factor(municipio)+as.factor(spanish.speakers)+as.factor(no.spanish.speaker)+as.factor(Aged.16.19)+as.factor(Aged.20.24)+as.factor(Aged.25.29)+as.factor(Aged.30.34)+as.factor(Aged.35.39)+as.factor(Aged.40.44)+as.factor(Aged.45.51)+as.factor(older61)+as.factor(responsabilities)+terminal(delta.censor),formula.terminalEvent=~u.rate+as.factor(h.skill)+as.factor(m.skill)+as.factor(municipio)+as.factor(spanish.speakers)+as.factor(no.spanish.speaker)+as.factor(Aged.16.19)+as.factor(Aged.20.24)+as.factor(Aged.25.29)+as.factor(Aged.30.34)+as.factor(Aged.35.39)+as.factor(Aged.40.44)+as.factor(Aged.45.51)+as.factor(older61)+as.factor(responsabilities),data=cr_05_males_services,n.knots=12,kappa1=1000,kappa2=1000,maxit=1000, Frailty=TRUE,joint=TRUE, recurrentAG=TRUE)
###The program took 3167.15 seconds

You should provide information what libraries do you use. I assume it is frailtypack but it maybe not obvious for everyone. Also your example is using cr_05_males_services you should provide some example how it looks like. — zero323, Sep 08 '13 at 10:12
Please add [necessary information on used packages](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example/5963610#5963610). Please check your code and data sets _carefully_. E.g. I suppose the `<` here `fit.joint.05_malesP — Henrik, Sep 08 '13 at 10:12

score 1 · Answer 1 · edited May 23 '17 at 12:11

1

Because you neither provide information about the packages used, nor the data necessary to run multivepenal or frailtyPenal, I can only help you with the Surv part (because I happened to have that package loaded).

The Surv warning message you provided (In Surv(.t0, .t, delta.stable) : Stop time must be > start time, NA created) suggests that something is strange with your variables .t0 (the time argument in Surv, refered to as 'start time' in the warning), and/or .t (time2 argument, 'Stop time' in the warning). I check this possibility with a simple example

# read the data you feed `Surv` with
df <- read.table(text = "row     id contadorbis unst. stable d.censor    .t0 .t
1   78  1   0   1   0   0   88
2   101 2   0   1   0   0   46
3   155 3   0   1   0   0   27
4   170 4   0   0   0   0   61
5   170 4   1   0   0   61  86
6   213 5   0   0   0   0   92
7   213 5   0   0   0   92  182
8   213 5   0   0   0   182 273
9   213 5   0   0   0   273 365
10  213 5   1   0   0   365 394
11  334 6   0   1   0   0   6
12  334 7   1   0   0   0   38
13  369 8   0   0   0   0   27
14  369 8   0   0   0   27  119
15  369 8   0   0   0   119 209
16  369 8   0   0   0   209 300
17  369 8   0   0   0   300 392", header = TRUE)

# create survival object
mysurv <- with(df, Surv(time = .t0, time2 = .t, event = stable))
mysurv

# create a new data set where one .t for some reason is less than .to
# on row five .t0 is 61, so I set .t to 60
df2 <- df
df2$.t[df2$.t == 86] <- 60

# create survival object using new data which contains at least one Stop time that is less than Start time
mysurv2 <- with(df2, Surv(time = .t0, time2 = .t, event = stable))

# Warning message:
#  In Surv(time = .t0, time2 = .t, event = stable) :
#  Stop time must be > start time, NA created
# i.e. the same warning message as you got

# check the survival object
mysurv2

# as you can see, the fifth interval contains NA
# I would recommend you check .t0 and .t in your data set carefully 
# one way to examine rows where Stop time (.t) is less than start time (.t0) is:
df2[which(df2$.t0 > df2$.t), ]

I am not familiar with multivepenal but it seems that it does not accept a survival object which contains intervals with NA, whereas might frailtyPenal might do so.

edited May 23 '17 at 12:11

Community

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answered Sep 08 '13 at 11:36

Henrik

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Thank you! Please add this information at the very start of your script in your question. Everything in the spirit of posting [a minimal, reproducible example](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example/5963610#5963610)! With the necessary **runnable code**, you are much more likely to receive a helpful answer. And since you are new on SO, you may [read this](http://meta.stackoverflow.com/help/someone-answers) to get an idea of what to do when someone answers your question. – Henrik Sep 08 '13 at 13:20
I have done what you suggested to my data frame and the answer is: 0 rows> (or 0-length row.names) in which .t<.t0 so I would appreciate more suggestions.I have included the libraries used and the link to my dataset. – user2739128 Sep 08 '13 at 14:07
In my tiny example, I explicitly told `Surv` to look for the variables in the data frame `df` and `df2` by using `with`. In your script, you are not referring to a specific data frame you call `Surv`. Is it possible that you have separate vectors called .t0, and .t laying around in your workspace that are used by `Surv`? I suggest you to start with a _clean workspace_, and run `Surv` in a first, separate step, specifically referring to the relevant data frame using `with` (similar to my small example). – Henrik Sep 08 '13 at 14:21
Sorry, a typo. Should be: "a specific data frame in your call to `Surv`" – Henrik Sep 08 '13 at 15:07
I have done this: df2 <- cr_05_males_serv mysurv2 <- with(df2, Surv(time = .t0, time2 = .t, event = delta.stable)) mysurv2 > mysurv2[which(.t0 > .t), ] [1] (,] Neither it is satisfied. – user2739128 Sep 08 '13 at 16:32
I am afraid I don't quite follow what you have done. Sorry. Can you please upload a text file with the data you are using in `Surv` to Dropbox. I have trouble with your the .rda file you posted before. – Henrik Sep 08 '13 at 16:46
I managed to download cr_05_males_serv.rda. ('data.frame':71205 obs. of 47 variables). No .t < .t0. I had no problems to run `with(cr_05_males_serv, Surv(time = .t0, time2 = .t, event = delta.stable))`. Have you tried to use this survival object in `multivePenal`? The error you received was from running **`Surv`**. If **I** don't get the errors when I run `Surv`, using the same variables, it seems likely you had variables lurking around on your workspace where some .t were < .t0. – Henrik Sep 08 '13 at 19:00
The problem comes when I run multivePenal(The code is in my question) and the answer that I received is that related with Survival.I really do not understand the mistake, because, as you have seen Survival is ok.Thank you very much for your help. – user2739128 Sep 08 '13 at 20:27
Yes, `Surv` runs fine **with the data set you posted**. But, I repeat, the warning message `Stop time must be > start time` comes from `Surv`. Thus, you must have used another dataset where a .t happened to be < .t0. – Henrik Sep 08 '13 at 20:58
I am using exactly that dataset. And for this dataset Surv runs well but multivepenal does not do, that is what I do not understand.Have you tried to run multivepenal with the dataset that works well with Surv??? I can not see what happen. – user2739128 Sep 09 '13 at 06:37

score 0 · Answer 2 · answered Sep 10 '13 at 10:22

0

The authors of the package have told me that the function is not finished yet, so perhaps that is the reason that it is not working well.

answered Sep 10 '13 at 10:22

user2739128

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score 0 · Answer 3 · answered Jan 23 '20 at 01:52

I encountered the same error and arrived at this solution.

frailtyPenal() will not accept data.frames of different length. The data.frame used in Surv and data.frame named in data= in frailtyPenal must be the same length. I used a Cox regression to identify the incomplete cases, reset the survival object to exclude the missing cases and, finally, run frailtyPenal:

library(survival)
library(frailtypack)

data(readmission)

#Reproduce the error

#change the first start time to NA
  readmission[1,3] <- NA 

#create a survival object with one missing time
  surv.obj1 <- with(readmission, Surv(t.start, t.stop, event))

#observe the error
  frailtyPenal(surv.obj1 ~ cluster(id) + dukes, 
               data=readmission, 
               cross.validation=FALSE,
               n.knots=10,
               kappa=1,
               hazard="Splines")

#repair by resetting the surv object to omit the missing value(s)

#identify NAs using a Cox model
  cox.na <- coxph(surv.obj1 ~ dukes, data = readmission)

#remove the NA cases from the original set to create complete cases
  readmission2 <- readmission[-cox.na$na.action,]

#reset the survival object using the complete cases
  surv.obj2 <- with(readmission2, Surv(t.start, t.stop, event))

#run frailtyPenal using the complete cases dataset and the complete cases Surv object
  frailtyPenal(surv.obj2 ~ cluster(id) + dukes,
               data = readmission2, 
               cross.validation = FALSE,
               n.knots = 10,
               kappa = 1,
               hazard = "Splines")

mistake in multivePenal but not in frailtyPenal

3 Answers3