FamEvent (version 1.3)

plot.penmodel: Plot method for penmodel

Description

Plots penetrance curves estimated from the fitted penetrance model and overlays non-parametric penetrance curves estimated from the data without proabands.

Usage

# S3 method for penmodel
plot(x, print=TRUE, mark.time=FALSE, conf.int=FALSE, …)

Arguments

x

An object class of penmodel, a fitted model by penmodel or penmodelEM functions.

print

Logical; if TRUE, displays parameter estimates and penetrance estimates by age 70.

mark.time

Logical; if TRUE, curves are marked at each censoring time, otherwise, no labeling is done.

conf.int

Logical; if TRUE, displays 95% confidence intervals for both parametric and non-parametric penetrance estimates for each subgroup and returns their lower and upper limits.

...

Other parameters to be passed through to plotting functions.

Value

It displays the following summary values:

coefficients

Parameter estimates of transformed baseline parameters (\(\lambda, \rho\)) and regression coefficients for gender and mutation status (\(\beta_s, \beta_g\)).

pen70

Penetrance estimates by age 70 specific to gender and mutation-status subgroups.

x.age

Vetor of ages of onsest ranging from agemin to 80 years

pen

Penetrance estimates at each age in x.age, specific to gender and mutation-status subgroups.

lower

Lower limits of 95% confidence interval estimates for penetrance at each age in x.age, specific to gender and mutation status subgroups.

upper

Upper limits of 95% confidence interval estimates for penetrance at each age in x.age, specific to gender and mutation status subgroups.

Details

The 95% confidence intervals for the parametric penetrance curves were obtained based on 1000 simulations of the parameters, assuming a multivariate normal distribution for the estimated parameters with their variance covariance matrix. See penci for more details.

See Also

penmodel, print.penmodel, penmodelEM, summary.penmodel, print.summary.penmodel,

simfam, penci, penf

Examples

# NOT RUN {
# Simulated family data  

fam <- simfam(N.fam=300, design="pop+", base.dist="Weibull", variation="none",
       base.parms=c(0.01,3), vbeta=c(-1.13, 2.35), allelefreq=0.02, agemin=20)
 
# Fit family data

fit <- penmodel(parms=c(0.01, 3), vbeta=c(-1.13, 2.35), data=fam, 
       design="pop+", base.dist="Weibull")
       
# Plot penetrance function curves

plot(fit)
	
# }