plot: Prognostic response plot (PR-plot) for 'anoint' class.

Description Details Methods Author(s) Examples

Description

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.

Details

Additional arguments are passed to glm or coxph.

Methods

plot

signature(object = "anoint",predict=NULL,fun=exp,...): Prognostic response plot.

Author(s)

S. Kovalchik s.a.kovalchik@gmail.com

Examples

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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)")

anoint documentation built on May 2, 2019, 3:26 p.m.

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