Abstract
We develop tests of the proportional hazards assumption, with respect
to a continuous covariate, in the presence of unobserved heterogeneity
with unknown distribution at the individual observation level.
The proposed tests are specially powerful against ordered alternatives
useful for modeling non-proportional hazards situations. By contrast
to the case when the heterogeneity distribution is known up to finite
dimensional parameters, the null hypothesis for the current problem
is similar to a test for absence of covariate dependence. However,
the two testing problems differ in the nature of relevant alternative
hypotheses. We develop tests for both the problems against ordered
alternatives. Small sample performance and an application to real
data highlight the usefulness of the framework and methodology.
to a continuous covariate, in the presence of unobserved heterogeneity
with unknown distribution at the individual observation level.
The proposed tests are specially powerful against ordered alternatives
useful for modeling non-proportional hazards situations. By contrast
to the case when the heterogeneity distribution is known up to finite
dimensional parameters, the null hypothesis for the current problem
is similar to a test for absence of covariate dependence. However,
the two testing problems differ in the nature of relevant alternative
hypotheses. We develop tests for both the problems against ordered
alternatives. Small sample performance and an application to real
data highlight the usefulness of the framework and methodology.
| Original language | English |
|---|---|
| Place of Publication | St. Andrews |
| Publisher | Scottish Institute for Research in Economics |
| Publication status | Published - 2009 |
Publication series
| Name | SIRE Discussion Papers |
|---|
Keywords
- two-sample tests
- increasing hazard ratio
- trend tests
- partial orders
- mixed proportional hazards model
- time varying coefficients