plot.penmodel_c: Plot method for 'penmodel_c'

In FamEvent: Family Age-at-Onset Data Simulation and Penetrance Estimation

Plot method for penmodel_c

Description

Plots penetrance curves for each event estimated from the fitted competing risks model and overlays non-parametric cumulative incidence curves estimated from the data without proabands.

Usage

## S3 method for class 'penmodel_c'
plot(x, agemax = 80, print = TRUE, conf.int = FALSE, 
add.CIF = TRUE, MC = 100, col = c("blue", "red", "blue", "red"), lty = c(1, 1, 2, 2), 
xlab = "Age at onset", ylab = "Penetrance", ylim = NULL,  ...)

Arguments

x	An object class of 'penmodel', a fitted model by penmodel or penmodelEM functions.
agemax	Maximum age of disease onset or maximum age. Default is 80 years of age.
print	Logical; if TRUE, displays parameter estimates and penetrance estimates by age 70.
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.
add.CIF	Logical; if TRUE, displays cumulative incidence curves from competing event data.
MC	Number of simulated samples used to calculate confidence intervals with a Monte-Carlo method. If MC = 0, no confidence intervals will be calculated. Default value is 100.
col	Colors of lines for male carriers, female carriers, male noncarrers, and female noncarriers. Default is c("blue", "red", "blue", "red").
lty	Types of lines for male carriers, female carriers, male noncarriers, and female noncarriers. Default is c(1, 1, 2, 2).
xlab	Title for the x-axis. Default is "Age at onset".
ylab	Title for the y-axis. Default is "Penetrance".
ylim	Limits for the y-axis. Default is NULL. If NULL, ylim will be automatically determined.
...	Other parameters to be passed through to plotting functions.

Details

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

Value

Returns the following summary values:

coefficients	Parameter estimates from the competing risks model.
pen70	Penetrance estimates by age 70, specific to gender and mutation-status subgroups.
age	Vector of ages of onsest ranging from agemin to agemax years
pen1	Penetrance estimates for event 1 at each age in age, specific to gender and mutation-status subgroups.
pen2	Penetrance estimates for event 2 at each age in age, specific to gender and mutation-status subgroups.
lower1	Lower limits of 95% confidence interval estimates for penetrance for event 1 at each age in age, specific to gender and mutation status subgroups.
upper1	Upper limits of 95% confidence interval estimates for penetrance for event 1 at each age in x.age, specific to gender and mutation status subgroups.
lower2	Lower limits of 95% confidence interval estimates for penetrance for event 2 at each age in age, specific to gender and mutation status subgroups.
upper2	Upper limits of 95% confidence interval estimates for penetrance for event 2 at each age in x.age, specific to gender and mutation status subgroups.

Author(s)

Yun-Hee Choi

See Also

penmodel_c, print.penmodel_c, summary.penmodel_c, print.summary.penmodel_c, simfam_c

Examples

## Not run: 
# Simulated family data  
set.seed(4321)
fam2 <- simfam_c(N.fam = 500, design = "pop+", variation = "frailty", competing=TRUE,
                  base.dist = "Weibull", frailty.dist = "cgamma", depend=c(2, 2, 2), 
                  allelefreq = 0.02, base.parms = list(c(0.01, 3), c(0.01, 3)), 
                  vbeta = list(c(-1.13, 2.35),c(-1, 2)))

# Fit family data
fit2 <- penmodel_c(formula1 = Surv(time, status==1)~ gender + mgene, 
                   formula2 = Surv(time, status==2)~ gender + mgene, 
                   cluster = "famID", gvar = "mgene", frailty.dist = "cgamma",
                   parms=list(c(0.01, 3, -1, 2.3), c(0.01, 3, -1, 2), c(2, 2, 2)), 
                   data=fam2, design="pop+", base.dist="Weibull", robust=TRUE)

# Plot penetrance function curves with 95
plot(fit2, conf.int=TRUE, MC=200, ylim=c(0, 0.7))


## End(Not run)

FamEvent documentation built on Nov. 17, 2022, 5:06 p.m.