[R] multinomial conditional logit models

[Friedrich.Leisch@univie.ac.at]

>>>>> On Wed, 29 Jan 2003 11:57:20 -0800 (PST),
>>>>> John Hendrickx (JH) wrote:

  > A multinomial logit model can be specified as a conditional logit
  > model after restructuring the data. Doing so gives flexibility in
  > imposing restrictions on the dependent variable. One application is
  > to specify a loglinear model for square tables, e.g. quasi-symmetry
  > or quasi-independence, as a multinomial logit model with covariates.
  > Further details on this technique and examples with several packages
  > are on my homepage at http://www.xs4all.nl/~jhckx/mcl/

  > I've been trying to implement an MCL model in R and have been mostly
  > succesful. However I'm still stuck on a few points and I'm hoping
  > someone can point out how to do fix them.

  > To estimate an MCL model, the data must be restructured into a
  > person-choice file. 

  > * Each case must be duplicated "ncat" times ("ncat" is the number of
  > categories of the dependent variable)
  > * Each case must be identified by a strata variable (id)
  > * Each duplicate must be identified by a variable indexing the
  > choices (newy)
  > * A dichotomous variable must indicate which duplicate corresponds
  > with the respondent's choice (didep)

I'm not completely sure if I understand your target format completely,
but it sounds like reshape() could do all you want:


R> df3
  id age dose1 dose2 dose4
1  1  40     1     2     3
2  2  50     2     1     3
3  3  60     1     2     3
4  4  50     2     1     3



R> reshape(df3, direction = "long", idvar=1,
           varying=list(dose=c("dose1", "dose2", "dose4")))

    id age time dose1
1.1  1  40    1     1
2.1  2  50    1     2
3.1  3  60    1     1
4.1  4  50    1     2
1.2  1  40    2     2
2.2  2  50    2     1
3.2  3  60    2     2
4.2  4  50    2     1
1.3  1  40    3     3
2.3  2  50    3     3
3.3  3  60    3     3
4.3  4  50    3     3


which is a (modified) example from help(reshape) ... there you find
much more examples.

Hope this helps,
Fritz

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