Derives the Brier Scores (using Inverse Probability of Censoring Weighting) for the Survival estimates as detailed in (Blanche et al. 2015) .
Usage
# S3 method for class 'SurvivalQuantities'
brierScore(object, maintain_cen_order = TRUE, event_offset = TRUE, ...)
Arguments
- object
(
SurvivalQuantities
)
survival quantities.- maintain_cen_order
(
logical
)
IfTRUE
then, in the case of ties, censor times are always considered to have occurred after the event times when calculating the "reverse Kaplan-Meier" for the IPCW estimates. Setting this toTRUE
mirrors the implementation of the{prodlim}
package.- event_offset
(
logical
)
IfTRUE
then \(G(T_i)\) is evaluated at \(G(T_i-)\). Setting this asTRUE
mirrors the implementation of the{pec}
package.- ...
not used.
References
Blanche P, Proust-Lima C, Loubère L, Berr C, Dartigues J, Jacqmin-Gadda H (2015). “Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.” Biometrics, 71(1), 102-113. doi:10.1111/biom.12232 , https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.12232, https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.12232.
See also
Other brierScore:
brierScore()
Other SurvivalQuantities:
SurvivalQuantities-class
,
as.data.frame.SurvivalQuantities()
,
autoplot.SurvivalQuantities()
,
summary.SurvivalQuantities()