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From |
Enzo Coviello <enzo.coviello@alice.it> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: new version of -stcoxgof- available from SSC |

Date |
Sat, 01 Dec 2007 18:54:13 +0100 |

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

Unità 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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