Checking Fine and Gray subdistribution hazards model with cumulative sums of residuals
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| 024 | 7 | 0 | |a 10.1007/s10985-014-9313-9 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s10985-014-9313-9 | ||
| 245 | 0 | 0 | |a Checking Fine and Gray subdistribution hazards model with cumulative sums of residuals |h [Elektronische Daten] |c [Jianing Li, Thomas Scheike, Mei-Jie Zhang] |
| 520 | 3 | |a Recently, Fine and Gray (J Am Stat Assoc 94:496-509, 1999) proposed a semi-parametric proportional regression model for the subdistribution hazard function which has been used extensively for analyzing competing risks data. However, failure of model adequacy could lead to severe bias in parameter estimation, and only a limited contribution has been made to check the model assumptions. In this paper, we present a class of analytical methods and graphical approaches for checking the assumptions of Fine and Gray's model. The proposed goodness-of-fit test procedures are based on the cumulative sums of residuals, which validate the model in three aspects: (1) proportionality of hazard ratio, (2) the linear functional form and (3) the link function. For each assumption testing, we provide a $$p$$ p -values and a visualized plot against the null hypothesis using a simulation-based approach. We also consider an omnibus test for overall evaluation against any model misspecification. The proposed tests perform well in simulation studies and are illustrated with two real data examples. | |
| 540 | |a Springer Science+Business Media New York, 2014 | ||
| 690 | 7 | |a Competing risk |2 nationallicence | |
| 690 | 7 | |a Goodness-of-fit |2 nationallicence | |
| 690 | 7 | |a Proportional subdistribution hazard |2 nationallicence | |
| 690 | 7 | |a Cumulative residual |2 nationallicence | |
| 690 | 7 | |a Link function |2 nationallicence | |
| 690 | 7 | |a Omnibus test |2 nationallicence | |
| 700 | 1 | |a Li |D Jianing |u Division of Biostatistics, Medical College of Wisconsin, Milwaukee, USA |4 aut | |
| 700 | 1 | |a Scheike |D Thomas |u Department of Biostatistics, University of Copenhagen, Copenhagen, Denmark |4 aut | |
| 700 | 1 | |a Zhang |D Mei-Jie |u Division of Biostatistics, Medical College of Wisconsin, Milwaukee, USA |4 aut | |
| 773 | 0 | |t Lifetime Data Analysis |d Springer US; http://www.springer-ny.com |g 21/2(2015-04-01), 197-217 |x 1380-7870 |q 21:2<197 |1 2015 |2 21 |o 10985 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10985-014-9313-9 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s10985-014-9313-9 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Li |D Jianing |u Division of Biostatistics, Medical College of Wisconsin, Milwaukee, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Scheike |D Thomas |u Department of Biostatistics, University of Copenhagen, Copenhagen, Denmark |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Zhang |D Mei-Jie |u Division of Biostatistics, Medical College of Wisconsin, Milwaukee, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Lifetime Data Analysis |d Springer US; http://www.springer-ny.com |g 21/2(2015-04-01), 197-217 |x 1380-7870 |q 21:2<197 |1 2015 |2 21 |o 10985 | ||