[R] strata() in clogit()

[Yuelin Li]

How can I get the log odds associated with the levels in strata()
within a clogit() model?  I'm running R-1.9.0 on a Linux platform.

I am using clogit() to run a Rasch model in Item Response Theory in
psychometrics.  Symbolically, the model is:

  logit(p_{j,k}) = \log({\Pr(p_{j,k}) \over \Pr(1-p_{j,k})}) =
   \theta_j - \alpha_k,

That is, the log odds of answering an test item correctly is a function
of the item difficulty (\theta_j) and the ability of individual
students (\alpha_k).  The following R syntax gives me the \theta
coefficients associated with items i5 to i17, but summary() does not
automatically summarize the log odds associated with the strata "id".
I suppose the log odds associated with strata(id) gives me \alpha_k.
But I can't seem to get them with summary().  Help is greatly
appreciated.

Yuelin Li.

---- my R syntax is -----------

      > exam2.clog<- clogit(resp ~ i5+i6+i7+i8+i9+i10+i11+i12+i13+i14+
				   i15+i16+i17+ strata(id), data=exam1.1)
      > summary(exam2.clog)
      Call:
      clogit(resp ~ i5 + i6 + i7 + i8 + i9 + i10 + i11 + i12 + i13 +
	  i14 + i15 + i16 + i17 + strata(id), data = exam1.1)

	n= 476

	   coef exp(coef) se(coef)     z       p
      i5  0.514      1.67    1.025 0.501 6.2e-01
      i6  0.923      2.52    0.991 0.931 3.5e-01
      i7  0.514      1.67    1.025 0.501 6.2e-01
      i8  1.875      6.52    0.955 1.964 5.0e-02

      [snip]

          exp(coef) exp(-coef) lower .95 upper .95
      i5       1.67   0.597954     0.224      12.5
      i6       2.52   0.397477     0.361      17.6

      Rsquare= 0.525   (max possible= 0.659 )
      Likelihood ratio test= 355  on 13 df,   p=0
      Wald test            = 108  on 13 df,   p=0
      Score (logrank) test = 277  on 13 df,   p=0