st: new version of -stcoxgof- available from SSC

[Enzo Coviello <enzo.coviello@alice.it>]

Dear Stata Users,

thanks to Kit Baum, a new version of -stcoxgof- 
is available from SSC. Stata 10 is required.

-stcoxgof- is a post-estimation command testing 
the goodness of fit after a Cox model.  So you 
must use this command after stcox.

Based on ideas similar to the Hosmer-Lemeshow 
test for logistic regression, three goodness of fit tests for Cox
proportional hazards model can be derived by 
adding group indicator variables to the model and testing the hypothesis
that the coefficients of the group indicator 
variables are zero via score, likelihood ratio or Wald test.

The first is the Moreau, O'Quigley, and Lellouch 
(MOL) test obtained by partitioning in intervals the time axis and
grouping the individuals based on their risk 
score. Then, indicator variables are generated as cross products of time
intervals with risk score groups and included in 
the model. The MOL test is an omnibus test and should detect any
violations of the PH model.

The second is the added variable version of test 
proposed by Moreau. O'Quigley, and Mesbah (MOM).  The time axis is
partitoned in intervals and indicator variables 
are generated by cross products of time intervals with each level of
the covariates in the model. The MOM test is 
designed to specifically detect violations of the proportional hazards
assumption. The fact that we might need to use a 
large number of added variables limits the use of the MOM test to the
case of Cox models with just a few categorical covariates.

The third test is proposed by Gronnesby and 
Borgan. The idea is to divide the observations into groups based on their
estimated risk score. Then, indicator variables 
for risk score groups are added to the model testing whether their
coefficients are zero. This test, like the MOL 
test, is an omnibus test but it is not appropriate when time-varying
covariates are included in the model.


Ancillary files allow to run an example illustrating the use of -stcoxgof-.


Reference
S. May and D. W. Hosmer. Hosmer and Lemeshow type 
goodness-of-fit statistics for the Cox proportional hazards model.
In: Advances in Survival Analysis: Handbook of 
Statistics Vol 23, edited by N. Balakrishnana and C. R. Rao, Amsterdam:
Elsevier, North-Holland, 2004, p. 383-394.


Enzo


Enzo Coviello
Unit� di Epidemiologia e Statistica ASL BARI
Piazza V.  Emanuele 14
70054 Giovinazzo (Bari)
Italy
tel./fax +39 080 3357867
mobile +39 347 5016 016


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