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Mendolia, Franco

2010-Aug-11 16:54 UTC

[R] Arbitrary number of covariates in a formula

Hello!

I have something like this:

test1 <- data.frame(intx=c(4,3,1,1,2,2,3), 
                   status=c(1,1,1,0,1,1,0), 
                   x1=c(0,2,1,1,1,0,0), 
                   x2=c(1,1,0,0,2,2,0), 
                   sex=c(0,0,0,0,1,1,1)) 
                   
and I can easily fit a cox model:

library(survival)
coxph(Surv(intx,status) ~ x1 + x2 + strata(sex),test1)

However, I want to write my own function, fit the model inside this function and
then do some further computations.

f <- function(time, event, stratum, covar )
{

  fit <- coxph(Surv(time,event) ~ covar[[1]] + covar[[2]] + strata(stratum))
  fit
  #... do some other stuff
}

attach(test1)
f(intx, status, sex, list(x1,x2))

This works fine when I have exactly two covariates. However, I would like to
have something that I can use with an arbitrary number of covariates. More
precisely, I need something more general than covar[[1]] + covar[[2]].

Any ideas?

Thanks,
Franco

Erik Iverson

2010-Aug-11 17:00 UTC

head link

[R] Arbitrary number of covariates in a formula

Are you for some reason against writing your function to accept a single 
argument, a formula, that you simply pass on to coxph?

Mendolia, Franco wrote:> Hello!
> 
> I have something like this:
> 
> test1 <- data.frame(intx=c(4,3,1,1,2,2,3), 
>                    status=c(1,1,1,0,1,1,0), 
>                    x1=c(0,2,1,1,1,0,0), 
>                    x2=c(1,1,0,0,2,2,0), 
>                    sex=c(0,0,0,0,1,1,1)) 
>                    
> and I can easily fit a cox model:
> 
> library(survival)
> coxph(Surv(intx,status) ~ x1 + x2 + strata(sex),test1)
> 
> However, I want to write my own function, fit the model inside this
function and then do some further computations.
> 
> f <- function(time, event, stratum, covar )
> {
> 
>   fit <- coxph(Surv(time,event) ~ covar[[1]] + covar[[2]] +
strata(stratum))
>   fit
>   #... do some other stuff
> }
> 
> attach(test1)
> f(intx, status, sex, list(x1,x2))
> 
> This works fine when I have exactly two covariates. However, I would like
to have something that I can use with an arbitrary number of covariates. More
precisely, I need something more general than covar[[1]] + covar[[2]].
> 
> Any ideas?
> 
> Thanks,
> Franco
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

Mendolia, Franco

2010-Aug-11 17:53 UTC

head link

[R] Arbitrary number of covariates in a formula

I could do that. However, the function f that I mentioned below is part of a
bigger program and is nested inside another function, say function A. In
function A I determine the covariates that I want to use and then call my
function f. So even if I use a formula as single argument, I would still need to
construct the formula with the arbitrary number of covariates which then leads
to my original problem.

________________________________________
From: Erik Iverson [eriki at ccbr.umn.edu]
Sent: Wednesday, August 11, 2010 12:00 PM
To: Mendolia, Franco
Cc: r-help at r-project.org
Subject: Re: [R] Arbitrary number of covariates in a formula

Are you for some reason against writing your function to accept a single
argument, a formula, that you simply pass on to coxph?

Mendolia, Franco wrote:> Hello!
>
> I have something like this:
>
> test1 <- data.frame(intx=c(4,3,1,1,2,2,3),
>                    status=c(1,1,1,0,1,1,0),
>                    x1=c(0,2,1,1,1,0,0),
>                    x2=c(1,1,0,0,2,2,0),
>                    sex=c(0,0,0,0,1,1,1))
>
> and I can easily fit a cox model:
>
> library(survival)
> coxph(Surv(intx,status) ~ x1 + x2 + strata(sex),test1)
>
> However, I want to write my own function, fit the model inside this
function and then do some further computations.
>
> f <- function(time, event, stratum, covar )
> {
>
>   fit <- coxph(Surv(time,event) ~ covar[[1]] + covar[[2]] +
strata(stratum))
>   fit
>   #... do some other stuff
> }
>
> attach(test1)
> f(intx, status, sex, list(x1,x2))
>
> This works fine when I have exactly two covariates. However, I would like
to have something that I can use with an arbitrary number of covariates. More
precisely, I need something more general than covar[[1]] + covar[[2]].
>
> Any ideas?
>
> Thanks,
> Franco
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

Henrique Dallazuanna

2010-Aug-11 18:26 UTC

head link

[R] Arbitrary number of covariates in a formula

This shoul work:

coxph(Surv(intx, status) ~ . + strata(sex) - sex, test1)


On Wed, Aug 11, 2010 at 1:54 PM, Mendolia, Franco <fmendolia@mcw.edu>
wrote:
> Hello!
>
> I have something like this:
>
> test1 <- data.frame(intx=c(4,3,1,1,2,2,3),
>                   status=c(1,1,1,0,1,1,0),
>                   x1=c(0,2,1,1,1,0,0),
>                   x2=c(1,1,0,0,2,2,0),
>                   sex=c(0,0,0,0,1,1,1))
>
> and I can easily fit a cox model:
>
> library(survival)
> coxph(Surv(intx,status) ~ x1 + x2 + strata(sex),test1)
>
> However, I want to write my own function, fit the model inside this
> function and then do some further computations.
>
> f <- function(time, event, stratum, covar )
> {
>
>  fit <- coxph(Surv(time,event) ~ covar[[1]] + covar[[2]] +
strata(stratum))
>  fit
>  #... do some other stuff
> }
>
> attach(test1)
> f(intx, status, sex, list(x1,x2))
>
> This works fine when I have exactly two covariates. However, I would like
> to have something that I can use with an arbitrary number of covariates.
> More precisely, I need something more general than covar[[1]] + covar[[2]].
>
> Any ideas?
>
> Thanks,
> Franco
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O

	[[alternative HTML version deleted]]

Bert Gunter

2010-Aug-11 18:37 UTC

head link

[R] Arbitrary number of covariates in a formula

suppose covnames is a vector containing your covariate names (e.g. as
character strings)

Then (warning: untested)

rhs <- paste(covnames, collapse="+")

## makes them into a single string separated by "+"-es and

form <- formula(paste("y", rhs, sep="~"))

## creates your formula.

?substitute can also be useful for this.

-- Bert Gunter
Genentech Nonclinical Biostatistics

On Wed, Aug 11, 2010 at 10:53 AM, Mendolia, Franco <fmendolia at mcw.edu>
wrote:>
> I could do that. However, the function f that I mentioned below is part of
a bigger program and is nested inside another function, say function A. In
function A I determine the covariates that I want to use and then call my
function f. So even if I use a formula as single argument, I would still need to
construct the formula with the arbitrary number of covariates which then leads
to my original problem.
>
> ________________________________________
> From: Erik Iverson [eriki at ccbr.umn.edu]
> Sent: Wednesday, August 11, 2010 12:00 PM
> To: Mendolia, Franco
> Cc: r-help at r-project.org
> Subject: Re: [R] Arbitrary number of covariates in a formula
>
> Are you for some reason against writing your function to accept a single
> argument, a formula, that you simply pass on to coxph?
>
> Mendolia, Franco wrote:
>> Hello!
>>
>> I have something like this:
>>
>> test1 <- data.frame(intx=c(4,3,1,1,2,2,3),
>> ? ? ? ? ? ? ? ? ? ?status=c(1,1,1,0,1,1,0),
>> ? ? ? ? ? ? ? ? ? ?x1=c(0,2,1,1,1,0,0),
>> ? ? ? ? ? ? ? ? ? ?x2=c(1,1,0,0,2,2,0),
>> ? ? ? ? ? ? ? ? ? ?sex=c(0,0,0,0,1,1,1))
>>
>> and I can easily fit a cox model:
>>
>> library(survival)
>> coxph(Surv(intx,status) ~ x1 + x2 + strata(sex),test1)
>>
>> However, I want to write my own function, fit the model inside this
function and then do some further computations.
>>
>> f <- function(time, event, stratum, covar )
>> {
>>
>> ? fit <- coxph(Surv(time,event) ~ covar[[1]] + covar[[2]] +
strata(stratum))
>> ? fit
>> ? #... do some other stuff
>> }
>>
>> attach(test1)
>> f(intx, status, sex, list(x1,x2))
>>
>> This works fine when I have exactly two covariates. However, I would
like to have something that I can use with an arbitrary number of covariates.
More precisely, I need something more general than covar[[1]] + covar[[2]].
>>
>> Any ideas?
>>
>> Thanks,
>> Franco
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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