roc for model
roc(...)# S3 method for cph
roc(..., times = NULL, model = NULL, x = NULL, method = c("NNE", "KM"))
# S3 method for coxph
roc(..., times = NULL, model = NULL, x = NULL, method = c("NNE", "KM"))
# S3 method for glm
roc(
...,
negref = 0,
model = NULL,
x = NULL,
method = c("empirical", "binormal", "nonparametric")
)
# S3 method for lrm
roc(
...,
negref = 0,
model = NULL,
x = NULL,
method = c("empirical", "binormal", "nonparametric")
)
one or more fit
one or more times for cox regression
can be logical or characters. FALSE means no model TP and FP, characters mean model names.
can be logical or characters. TRUE means all x variable in regression will be calculated. One or more characters will be calculated only.
NNE or KM
negative reference for each model
roc dataframe
one roc_coxph for cox regression. model means model names,
Heagerty PJ, Lumley T, Pepe MS. Time-dependent ROC curves for censored survival data and a diagnostic marker. Biometrics, 2000.
Pepe, Margaret Sullivan. The statistical evaluation of medical tests for classification and prediction. Medicine, 2003.
Zou, Kelly H., W. J. Hall, and David E. Shapiro. Smooth non-parametric receiver operating characteristic (ROC) curves for continuous diagnostic tests. Statistics in medicine 16, no. 19 (1997): 2143-2156.