plot {anoint} | R Documentation |
anoint
class.Computes the prognostic score (baseline risk) based on the covariates of anoint
or a supplied set of predictions. Risk scores are binned into ten groups based on risk deciles and a treatment effect (and confidence interval) is estimated in each group. This is compared to the overall treatment effect which is indicated by the shaded region.
Additional arguments are passed to glm
or coxph
.
signature(object = "anoint",predict=NULL,fun=exp,...)
:
Prognostic response plot.
S. Kovalchik s.a.kovalchik@gmail.com
set.seed(11903)
# BINOMIAL EVENT DATA WITH 4 NORMAL PROGNOSTIC FACTORS
pim.interaction <- data.anoint(
alpha = c(log(.2/.8),log(.2*.75/(1-.2*.75))),
beta = log(c(1.5,1.1,2,1.3)),
gamma = rep(1.5,4),
mean = rep(0,4),
vcov = diag(4),
type="binomial", n = 500
)
object <- anoint(y~(V1+V2+V3+V4)*trt,data=pim.interaction)
plot(object,bty="n",las=1)
# PLOT TREATMENT EFFECT ON LINEAR PREDICTOR SCALE
plot(object,fun=function(x)x,bty="n",las=1,ylab="treatment effect (linear predictor)")