residuals.coxph_mpl | R Documentation |
Compute martingale and Cox and Snell residuals for a model fitted
by coxph_mpl
. Return objects are of class
residuals.coxph_mpl
and have methods for plot
.
## S3 method for class 'coxph_mpl' residuals(object, ...) ## S3 method for class 'residuals.coxph_mpl' plot(x, ask=TRUE, which=1:2, upper.quantile=.95, ...)
object |
an object inheriting from class |
x |
an object inheriting from class |
ask |
logical. If |
which |
integer vector indicating the list of wished plots. If a subset of the plots
is required, specify a subset of the numbers |
upper.quantile |
quantile of the Cox and Snell residuals used when |
... |
other parameters to be passed through to plotting or printing functions. |
Refer to Collet (2003, Chapter 4) for a review of model check in the Cox regression model, and specifically to Farrington (2000) for an overview on residuals with interval-censored survival data.
For object of class residuals.coxph_mpl
, the available residual plots
are, respectively, the martingale residual plot (which==1
) and
the Cox and Snell residual plot (which==2
).
A data.frame of class residuals.coxph_mpl
of n rows
with following columns:
'time1'
, the model outcome (with a random noise
added to event ties if ties=='epsilon'
in coxph_mpl.control
);
'time2'
, ending time of the interval for interval censored data only (unused otherwise);
'censoring'
, the status indicator as in the Surv()
function, i.e. 0=right censored, 1=event at time, 2=left censored, 3=interval censored;
'coxsnell'
, the Cox and Snell residuals;
'martingale'
, the martingale residuals.
Dominique-Laurent Couturier, Maurizio Manuguerra
Farrington C.P. (2000), Residuals for Proportional Hazard Models with Interval-Censored Data, Biometrics 56, 473-482.
Collett, D. (2003), and Moeschberger, M. L. (2003), Modelling Survival Data in Medical Research, Chapman and All.
coxph_mpl
, coxph_mpl.control
,
coxph_mpl.object
, predict.coxph_mpl
and
summary.coxph_mpl
.
## Not run: ### lung data of the survival package (see ?lung) data(lung) fit_mpl <- coxph_mpl(Surv(time, status == 2) ~ age + sex + ph.karno + wt.loss, data = lung) par(mfrow=c(1,2)) plot(residuals(fit_mpl), which=1:2, ask=FALSE) ## End(Not run)
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