R help - Nov 2017 - Bootstrap analysis from a conditional logistic regression

Nelly Reduan a partag? un fichier OneDrive avec vous. Pour l?afficher, cliquez
sur le lien ci-dessous.


<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb>
[https://r1.res.office365.com/owa/prem/images/dc-png_20.png]<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb>

Screenshot 2017-11-12
18.49.43.png<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb>




Hello

How can I perform a bootstrap analysis from a conditional logistic regression?
The model has been built using the `clogit` function (`survival` package)? The
model has the following structure:

    mod <- clogit(event ~ forest + log_area +forest:log_time  +
cluster(ID_individual)  +   strata(ID_strata), method = "efron", data
= data , x=T, y=T)

Using bootstrapping, I would like to have a measure of uncertainty around the
estimates of beta coefficients.

I am using the following code but I don't know how to consider strata and
cluster arguments.

    library(boot)
    boot.clogit <- function(data, indices){
      new_data <- data[indices,]
      mod <- clogit(event ~ forest + log_area + forest:log_time  +
cluster(ID_individual)  +  strata(ID_strata),
                    method = "efron", data = new_data, x=T, y=T)
      coefficients(mod)
    }

    boot_data <- boot(data=data, statistic=boot.clogit, R=5000)

I have attached an overview of my data set.

Thank you very much for your time.
Best regards,
Nell






	[[alternative HTML version deleted]]

> On Nov 13, 2017, at 2:01 PM, Nelly Reduan <nell.redu at hotmail.fr>
wrote:
> 
> Nelly Reduan a partag? un fichier OneDrive avec vous. Pour l?afficher,
cliquez sur le lien ci-dessous.
> 
> 
> <https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb>
>
[https://r1.res.office365.com/owa/prem/images/dc-png_20.png]<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb>
> 
> Screenshot 2017-11-12
18.49.43.png<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb>
> 
> 
> 
> 
> Hello
> 
> How can I perform a bootstrap analysis from a conditional logistic
regression? The model has been built using the `clogit` function (`survival`
package)? The model has the following structure:
> 
>    mod <- clogit(event ~ forest + log_area +forest:log_time  +
cluster(ID_individual)  +   strata(ID_strata), method = "efron", data
= data , x=T, y=T)
> 
> Using bootstrapping, I would like to have a measure of uncertainty around
the estimates of beta coefficients.
> 
> I am using the following code but I don't know how to consider strata
and cluster arguments.
> 
>    library(boot)
>    boot.clogit <- function(data, indices){
>      new_data <- data[indices,]
>      mod <- clogit(event ~ forest + log_area + forest:log_time  +
cluster(ID_individual)  +  strata(ID_strata),
>                    method = "efron", data = new_data, x=T, y=T)
>      coefficients(mod)
>    }
> 
>    boot_data <- boot(data=data, statistic=boot.clogit, R=5000)
> 
> I have attached an overview of my data set.
You probably tried to attach something but you failed to note the section in the
listinfo or posting guide where the list owners describe the rules for
attachments. I think you would need to describe the sampling design more
thoroughly. A simple description of the data layout may not be sufficient.

 The fact that you are clustering on individuals suggests you have some sort of
repeated measures design and that you have somehow matched the individual to
controls in some unstated ratio (handled by the strata. (Admittedly all
guesswork and the more knowledgeable respondents (among which I'm not likely
to reside)  are often hesitant to contribute substantive commentary unless they
can narrow down range of possible design issues. I read Davison and Hinkley as
suggesting that sampling by group but then keeping sampled groups undisturbed
may have better chance of resulting in estimates of variances that match the
superpopulation. See pages 100-102 of their book.

If my reading of that section is correct then I should think you would arrange
you data so groups are in the long direction and single groups occupy a line of
data with a single index. Then you would probably rearrange the data within the
boot.clogit function so that the "inner" clogit call can handle it
correctly.

-- 
David.
> 
> Thank you very much for your time.
> Best regards,
> Nell
> 
> 
> 
> 
> 
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
David Winsemius
Alameda, CA, USA

'Any technology distinguishable from magic is insufficiently advanced.' 
-Gehm's Corollary to Clarke's Third Law