@article{PAR00015078,
  title = {{A} {L}og-{R}ank-{T}ype test to compare net survival distributions},
  author = {{G}raffeo, {N}. and {C}astell, {F}. and {B}elot, {A}. and {G}iorgi, {R}och},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n population-based cancer studies, it is often interesting to compare cancer survival between different populations. {H}owever, in such studies, the exact causes of death are often unavailable or unreliable. {N}et survival methods were developed to overcome this difficulty. {N}et survival is the survival that would be observed if the disease under study was the only possible cause of death. {T}he {P}ohar-{P}erme estimator ({PPE}) is a nonparametric consistent estimator of net survival. {I}n this article, we present a log-rank-type test for comparing net survival functions (as estimated by {PPE}) between several groups. {W}e put the test within the counting process framework to introduce the inverse probability weighting procedure as required by the {PPE}. {W}e built a stratified version to control for categorical covariates that affect the outcome. {W}e performed simulation studies to evaluate the performance of this test and worked an application on real data.},
  keywords = {{C}ancer ; {L}og-rank ; {N}et survival ; {P}ohar-{P}erme estimator ; {S}tochastic ; process {T}est},
  booktitle = {},
  journal = {{B}iometrics},
  volume = {72},
  numero = {3},
  pages = {760--769},
  ISSN = {0006-341{X}},
  year = {2016},
  DOI = {10.1111/biom.12477},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00015078},
}