We present a statistical model and semiparametric estimation procedure for analysis of survival data with multiple cross-effects (MCE) of survival functions. A goodness-of-fit test for the proportional hazards model against the MCE model is proposed.
On propose un modèle et une procédure semiparamétrique d'estimation pour analyser les données de survie avec multiples effets de croisement (MCE) de fonctions de survie. Un test d'ajustement pour le modèle des risques proportionnels contre le modèle MCE est proposé.
Accepted:
Published online:
Vilijandas Bagdonavičius 1; Mikhail Nikulin 2
@article{CRMATH_2005__340_5_377_0, author = {Vilijandas Bagdonavi\v{c}ius and Mikhail Nikulin}, title = {Statistical analysis of survival and reliability data with multiple crossings of survival functions}, journal = {Comptes Rendus. Math\'ematique}, pages = {377--382}, publisher = {Elsevier}, volume = {340}, number = {5}, year = {2005}, doi = {10.1016/j.crma.2005.01.019}, language = {en}, }
TY - JOUR AU - Vilijandas Bagdonavičius AU - Mikhail Nikulin TI - Statistical analysis of survival and reliability data with multiple crossings of survival functions JO - Comptes Rendus. Mathématique PY - 2005 SP - 377 EP - 382 VL - 340 IS - 5 PB - Elsevier DO - 10.1016/j.crma.2005.01.019 LA - en ID - CRMATH_2005__340_5_377_0 ER -
%0 Journal Article %A Vilijandas Bagdonavičius %A Mikhail Nikulin %T Statistical analysis of survival and reliability data with multiple crossings of survival functions %J Comptes Rendus. Mathématique %D 2005 %P 377-382 %V 340 %N 5 %I Elsevier %R 10.1016/j.crma.2005.01.019 %G en %F CRMATH_2005__340_5_377_0
Vilijandas Bagdonavičius; Mikhail Nikulin. Statistical analysis of survival and reliability data with multiple crossings of survival functions. Comptes Rendus. Mathématique, Volume 340 (2005) no. 5, pp. 377-382. doi : 10.1016/j.crma.2005.01.019. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2005.01.019/
[1] Statistical Models Based on Counting Processes, Springer, New York, 1993
[2] Accelerated Life Models: Modeling and Statistical Analysis, Chapman and Hall/CRC, Boca Raton, 2002
[3] Analysis of survival data with cross-effects of survival functions, Biostatistics, Volume 5 (2004) no. 3, pp. 415-425
[4] C. Ceci, L. Mazliak, Optimal design in nonparametric life testing, Preprint January 2002, Laboratoire de probabilités et modèles aléatoirs, Universités Paris VI et VII, 2002
[5] On heteroscedastic hazards regression models: theory and application, J. Roy. Statist. Soc. Ser. B, Volume 63 (2001), pp. 63-79
[6] Counting Processes and Survival Analysis, Wiley, New York, 1991
[7] Survival Analysis. Statistics for Biology and Health, Springer, New York, 1997
[8] Clinical Trials: A Methodologic Perspective, Wiley, New York, 1997
[9] Effect of ignoring heterogeneity in hazards regression, Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life, Birkhäuser, Boston, 2004, pp. 239-252
[10] H.-D.I. Wu, A partial score test for difference among heteroscedastic populations, Preprint of The School of Public Health, China Medical College, Taichung, Taiwan, 21 October, 2002
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