[R] clogit and general conditional logistic regression

[(Ted Harding)]

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.
> 
> 
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> Date: 10-Dec-02                                       Time: 11:35:16
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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: 16:06:15
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