FamEvent (version 2.1)

summary.penmodel: Summary method for class penmodel

Description

Provides a summary of a fitted penetrance model.

Usage

# S3 method for penmodel
summary(object, correlation=FALSE, …)

Arguments

object

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

correlation

Logical; if TRUE, returns the correlation matrix of the estimated parameters. Default is FALSE.

...

Further arguments passed to or from other methods.

Value

Returns the object of class 'summary.penmodel', including the following summary values:

estimates

List of parameter estimates of transformed baseline parameters and regression coefficients, their standard errors, their robust standard errors if robust=TRUE was selected when fitting the penetrance model, \(t\)-statistics and corresponding two-sided \(p\)-values.

varcov

Variance-covariance matrix of the parameter estimates.

varcov.robust

Robust variance-covariance matrix of the parameter estimates if robust = TRUE was selected when fitting the penetrance model.

correlation

Correlation matrix obtained from the variance-covariance matrix.

correlation.robust

Correlation matrix obtained from the robust variance-covariance matrix if robust = TRUE was selected when fitting the penetrance model.

See Also

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

Examples

# NOT RUN {
# Simulated family data 

set.seed(4321)
fam <- simfam(N.fam = 200, design = "pop+", variation = "none", base.dist = "Weibull", 
       base.parms = c(0.01, 3), vbeta = c(-1.13, 2.35), agemin = 20, allelefreq = 0.02)
 
# Penetrance model fit for the simulated family data

fit <- penmodel(Surv(time, status) ~ gender + mgene, cluster = "famID", 
       parms=c(0.01, 3, -1.13, 2.35), data = fam, design = "pop+", base.dist = "Weibull")

# Summary of the model parameter and penetrance estimates from model fit

summary(fit)

# }
# NOT RUN {
Estimates: 
            Estimate Std. Error t value Pr(>|t|)  
log(lambda)   -4.531    0.08583 -52.793  0.01206 *
log(rho)       1.113    0.04688  23.737  0.02680 *
gender        -1.302    0.19233  -6.768  0.09339 .
mgene          2.349    0.23825   9.859  0.06436 .
Signif. codes:   0 '***'  0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
# }
# NOT RUN {
# }