R help - Dec 2002 - clogit and general conditional logistic regression

Can someone clarify what I cannot make out from the
documentation?

The function 'clogit' in the 'survival' package is
described as performing a "conditional logistic regression".
Its return value is stated to be "an object of class clogit
which is a wrapper for a coxph object."

This suggests that its usefulness is confined to the sort of
data which arise in survival/proportional hazard applications.

My question is: is 'clogit' capable of a general conditional
logistic analysis?

E.g. given a set of data on binomial experiments with Y=1
r_i times out of n_i, associated with levels A_i and B_i
of factors A and B at N_A and N_B levels, would

  clogit(Y ~ A+B, method=c(Exact"))

generate something sensible containing the results of a standard
exact conditional logistic regression of Y on A and B?

With thanks,
Ted.


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E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk>
Fax-to-email: +44 (0)870 167 1972
Date: 10-Dec-02                                       Time: 11:35:16
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Hi Ted,
The conditional exact (log)-Lik for a conditional logistic model (i.e. data
with matched pairs), and the exact (log)-Lik for a PH Cox model are *the
same* (1 matched pair== risk set), therefore clogit() is a wrapper for
coxph() (You can estimate conditional logistic model by means of coxph())
> My question is: is 'clogit' capable of a general conditional
> logistic analysis?
Yes, however I don't know if "general" means something else that I
ignore,

best,
vito



----- Original Message -----
From: "Ted Harding" <Ted.Harding at nessie.mcc.ac.uk>
To: <r-help at stat.math.ethz.ch>
Sent: Tuesday, December 10, 2002 12:35 PM
Subject: [R] clogit and general conditional logistic regression

> Can someone clarify what I cannot make out from the
> documentation?
>
> The function 'clogit' in the 'survival' package is
> described as performing a "conditional logistic regression".
> Its return value is stated to be "an object of class clogit
> which is a wrapper for a coxph object."
>
> This suggests that its usefulness is confined to the sort of
> data which arise in survival/proportional hazard applications.
>
> My question is: is 'clogit' capable of a general conditional
> logistic analysis?
>
> E.g. given a set of data on binomial experiments with Y=1
> r_i times out of n_i, associated with levels A_i and B_i
> of factors A and B at N_A and N_B levels, would
>
>   clogit(Y ~ A+B, method=c(Exact"))
>
> generate something sensible containing the results of a standard
> exact conditional logistic regression of Y on A and B?
>
> With thanks,
> Ted.
>
>
> --------------------------------------------------------------------
> E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk>
> Fax-to-email: +44 (0)870 167 1972
> Date: 10-Dec-02                                       Time: 11:35:16
> ------------------------------ XFMail ------------------------------
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> http://www.stat.math.ethz.ch/mailman/listinfo/r-help

On Tue, 10 Dec 2002 Ted.Harding at nessie.mcc.ac.uk wrote:
> Can someone clarify what I cannot make out from the
> documentation?
>
> The function 'clogit' in the 'survival' package is
> described as performing a "conditional logistic regression".
> Its return value is stated to be "an object of class clogit
> which is a wrapper for a coxph object."
>
> This suggests that its usefulness is confined to the sort of
> data which arise in survival/proportional hazard applications.
>
> My question is: is 'clogit' capable of a general conditional
> logistic analysis?
Yes.

> E.g. given a set of data on binomial experiments with Y=1
> r_i times out of n_i, associated with levels A_i and B_i
> of factors A and B at N_A and N_B levels, would
>
>   clogit(Y ~ A+B, method=c(Exact"))
>
> generate something sensible containing the results of a standard
> exact conditional logistic regression of Y on A and B?
Well, you need a stratum variable -- conditional logistic regression is
for matched sets. If you don't have strata it's just a very slow way of
doing logistic regression.  Also, when it says `exact' it means it's
using
the exact conditional likelihood, not that it is doing permutation tests
the way LogXact does.

Look at the example on the help page. It has data from a matched
case-control study with two predictors and a stratifying variable. The
example has the variables (with values 0,1,2) in a linear term, but you
could use factor() around them if you wanted to.

The conditional likelihood for logistic regression is (proportional to)
the partial likelihood for a stratified Cox model in which the event times
are all the same. That's why it works and why it's in the survival
package.


	-thomas

Thanks to Vito Muggeio & Tony Rossini for pointing out that
the form of the partial likelihood in the Cox PH model and
the conditional logistic regression model are the same.

However, that is a theoretical truth! What I was really
asking (and apologies if it was not clear) was whether
(and, if so, how) it would be possible to present the sort
of data I was referring to to the R function 'coxph' or
'clogit'; the documentation seems to assume data involving
a time component in a survival context, and I find I am
confused about how to escape from that context into the
more general regression (logistic linear model) context, when
using these functions in R.

Specifically, suppose I have data (say in the form of vectors)

  A = Level of categorical factor A
  X = Value of quantitative covariate X
  Cases = Number of Cases, r_i, out of n_i
  Unaffected = Number of Unaffected, (n_i - r_i), out of n_i

(no "time" involved here) and I want to fit, by conditional
logistic regression, a model such as

  Cases ~ A + X

How, then, may such data be presented to say 'coxph'?

Might the trick simply be to give every row an extra quasi-start-time
equal to 0, and a quasi-end-time equal to 1?

With thanks,
Ted.

On 10-Dec-02 Ted Harding wrote:
> Can someone clarify what I cannot make out from the
> documentation?
> 
> The function 'clogit' in the 'survival' package is
> described as performing a "conditional logistic regression".
> Its return value is stated to be "an object of class clogit
> which is a wrapper for a coxph object."
> 
> This suggests that its usefulness is confined to the sort of
> data which arise in survival/proportional hazard applications.
> 
> My question is: is 'clogit' capable of a general conditional
> logistic analysis?
> 
> E.g. given a set of data on binomial experiments with Y=1
> r_i times out of n_i, associated with levels A_i and B_i
> of factors A and B at N_A and N_B levels, would
> 
>   clogit(Y ~ A+B, method=c(Exact"))
> 
> generate something sensible containing the results of a standard
> exact conditional logistic regression of Y on A and B?
> 
> With thanks,
> Ted.
> 
> 
> --------------------------------------------------------------------
> E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk>
> Fax-to-email: +44 (0)870 167 1972
> Date: 10-Dec-02                                       Time: 11:35:16
> ------------------------------ XFMail ------------------------------
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> http://www.stat.math.ethz.ch/mailman/listinfo/r-help
--------------------------------------------------------------------
E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk>
Fax-to-email: +44 (0)870 167 1972
Date: 10-Dec-02                                       Time: 16:06:15
------------------------------ XFMail ------------------------------