For the Cox regression model, the partial likelihood functions involve linear combinations of induced order statistics. Some invariance principles pertaining to such linear combinations of induced order statistics are studied and the theory is incorporated in the formulation of some repeated significance tests (for the hypothesis of no regression) based on these partial likelihoods.
Publié le : 1981-01-14
Classification:
Analysis of covariance,
contiguity of probability measures,
Cox regression model,
hazard rate,
induced order statistics,
invariance principles,
quantile processes,
repeated significance tests,
surivival functions,
Wiener processes,
withdrawals,
60B10,
60F05,
62G99
@article{1176345336,
author = {Sen, Pranab Kumar},
title = {The Cox Regression Model, Invariance Principles for Some Induced Quantile Processes and Some Repeated Significance Tests},
journal = {Ann. Statist.},
volume = {9},
number = {1},
year = {1981},
pages = { 109-121},
language = {en},
url = {http://dml.mathdoc.fr/item/1176345336}
}
Sen, Pranab Kumar. The Cox Regression Model, Invariance Principles for Some Induced Quantile Processes and Some Repeated Significance Tests. Ann. Statist., Tome 9 (1981) no. 1, pp. 109-121. http://gdmltest.u-ga.fr/item/1176345336/