R: Summarizing Flexible Relative Survival Model Fits
summary.flexrsurv
R Documentation
Summarizing Flexible Relative Survival Model Fits
Description
summary methods for class flexrsurv.
Produces and prints summaries of the results of a fitted Relative Survival Model
Usage
## S3 method for class 'flexrsurv'
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)
## S3 method for class 'summary.flexrsurv'
print(x, digits = max(3L, getOption("digits") - 3L),
symbolic.cor = x$symbolic.cor,
signif.stars = getOption("show.signif.stars"), ...)
Arguments
object
an object of class "flexrsurv", usually, a result of a call to flexrsurv.
x
an object of class "summary.flexrsurv", usually, a result of a call to summary.flexrsurv.
correlation
logical; if TRUE, the correlation matrix of
the estimated parameters is returned and printed.
symbolic.cor
logical. If TRUE, print the correlations in
a symbolic form (see symnum) rather than as numbers.
digits
the number of significant digits to use when printing.
signif.stars
logical. If TRUE,'significance stars' are printed for each coefficient.
...
further arguments passed to or from other methods.
Details
print.summary.glm tries to be smart about formatting the coefficients, standard errors, etc.
and additionally gives ‘significance stars’ if signif.stars is TRUE.
Correlations are printed to two decimal places (or symbolically): to see the actual correlations
print summary(object)$correlation directly.
The dispersion of a GLM is not used in the fitting process, but it is needed to find standard
errors. If dispersion is not supplied or NULL, the dispersion is taken as 1 for the binomial and
Poisson families, and otherwise estimated by the residual Chisquared statistic (calculated from
cases with non-zero weights) divided by the residual degrees of freedom.
Value
The function summary.flexrsurv computes and returns a list of summary statistics of the fitted flexible relative survival model given in object.
The returned value is an object of class "summary.flexrsurv", which a list with components:
call
the "call" component from object.
terms
the "terms" component from object.
coefficients
the matrix of coefficients, standard errors, z-values and p-values.
cov
the estimated covariance matrix of the estimated coefficients.
correlation
(only if correlation is true.) the estimated correlations of the estimated coefficients.
symbolic.cor
(only if correlation is true.) the value of the argument symbolic.cor.
loglik
the "loglik" component from object.
df.residual
the "df.residual" component from object.
Examples
## Not run:
# data from package relsurv
data(rdata, package="relsurv")
# rate table from package relsurv
data(slopop, package="relsurv")
# get the death rate from slopop for rdata
rdata$iage <- findInterval(rdata$age*365.24, attr(slopop, "cutpoints")[[1]])
rdata$iyear <- findInterval(rdata$year, attr(slopop, "cutpoints")[[2]])
therate <- rep(-1, dim(rdata)[1])
for( i in 1:dim(rdata)[1]){
therate[i] <- slopop[rdata$iage[i], rdata$iyear[i], rdata$sex[i]]
}
rdata$slorate <- therate
# change sex coding
rdata$sex01 <- rdata$sex -1
# fit a relative survival model with a non linear effetc of age
fit <- flexrsurv(Surv(time,cens)~sex01+NLL(age, Knots=60, Degree=3),
rate=slorate, data=rdata,
knots.Bh=1850, # one interior knot at 5 years
degree.Bh=3,
Spline = "b-spline",
initbyglm=TRUE,
initbands=seq(from=0, to=5400, by=200)
int_meth= "CAV_SIM",
step=50
)
summary(fit)
## End(Not run)