I have the survival time for two groups and 7 units and I suspect that there is an interaction between some of the units and group. Univariate analysis shows there to be a difference in the survival curves for group and unit, but the KM plot shows that the assumption of proportional hazards does not hold for unit, and this is confirmed by:
stcox i.unit
. estat phtest, det
Test of proportional-hazards assumption
Time: Time
----------------------------------------------------------------
| rho chi2 df Prob>chi2
------------+---------------------------------------------------
1b.unit | . . 1 .
2.unit | -0.07373 1.47 1 0.2258
3.unit | -0.09501 2.41 1 0.1206
4.unit | -0.10126 2.78 1 0.0954
5.unit | -0.02570 0.18 1 0.6686
6.unit | -0.21703 13.39 1 0.0003
7.unit | -0.06441 1.11 1 0.2915
------------+---------------------------------------------------
global test | 16.11 6 0.0132
----------------------------------------------------------------
and
stcox i.group i.unit
. estat phtest
Test of proportional-hazards assumption
Time: Time
----------------------------------------------------------------
| chi2 df Prob>chi2
------------+---------------------------------------------------
global test | 17.85 7 0.0127
----------------------------------------------------------------
but when I include the interaction term
stcox i.group##i.unit
. estat phtest
Test of proportional-hazards assumption
Time: Time
----------------------------------------------------------------
| chi2 df Prob>chi2
------------+---------------------------------------------------
global test | 14.19 13 0.3607
----------------------------------------------------------------
there is no problem with the assumption of proportional hazards, and comparing the two models with lrtest shows the interaction term to be significant.
My query is - can I use the interaction model in a Cox regression when one of the main terms violates the PH assumption and my model comparison is based on this assumption, or should I go straight to a parametric regression, streg, where I will have to base the selection of the distribution on Information Criteria as I have no theoretical basis for choosing a distribution. Or is there an alternative approach that I could use?
Eddy
stcox i.unit
. estat phtest, det
Test of proportional-hazards assumption
Time: Time
----------------------------------------------------------------
| rho chi2 df Prob>chi2
------------+---------------------------------------------------
1b.unit | . . 1 .
2.unit | -0.07373 1.47 1 0.2258
3.unit | -0.09501 2.41 1 0.1206
4.unit | -0.10126 2.78 1 0.0954
5.unit | -0.02570 0.18 1 0.6686
6.unit | -0.21703 13.39 1 0.0003
7.unit | -0.06441 1.11 1 0.2915
------------+---------------------------------------------------
global test | 16.11 6 0.0132
----------------------------------------------------------------
and
stcox i.group i.unit
. estat phtest
Test of proportional-hazards assumption
Time: Time
----------------------------------------------------------------
| chi2 df Prob>chi2
------------+---------------------------------------------------
global test | 17.85 7 0.0127
----------------------------------------------------------------
but when I include the interaction term
stcox i.group##i.unit
. estat phtest
Test of proportional-hazards assumption
Time: Time
----------------------------------------------------------------
| chi2 df Prob>chi2
------------+---------------------------------------------------
global test | 14.19 13 0.3607
----------------------------------------------------------------
there is no problem with the assumption of proportional hazards, and comparing the two models with lrtest shows the interaction term to be significant.
My query is - can I use the interaction model in a Cox regression when one of the main terms violates the PH assumption and my model comparison is based on this assumption, or should I go straight to a parametric regression, streg, where I will have to base the selection of the distribution on Information Criteria as I have no theoretical basis for choosing a distribution. Or is there an alternative approach that I could use?
Eddy
Comment