xhaz (version 2.1.0)

print.bsplines: A print.bsplines Function used to print a object of class bsplines

Description

This function present the estimated coefficients for the excess hazard baseline coefficient and for the covariate effects

Usage

# S3 method for bsplines
print(x, digits = max(options()$digits - 4, 3), ...)

Value

Estimated parameters of the model in different scales for interpretation purposes.

Arguments

x

an object of class bsplines

digits

minimal number of significant digits.

...

additionnal parameters which can be used in the print function

References

Goungounga JA, Touraine C, Graff\'eo N, Giorgi R; CENSUR working survival group. Correcting for misclassification and selection effects in estimating net survival in clinical trials. BMC Med Res Methodol. 2019 May 16;19(1):104. doi: 10.1186/s12874-019-0747-3. PMID: 31096911; PMCID: PMC6524224. (PubMed)

Touraine C, Graff\'eo N, Giorgi R; CENSUR working survival group. More accurate cancer-related excess mortality through correcting background mortality for extra variables. Stat Methods Med Res. 2020 Jan;29(1):122-136. doi: 10.1177/0962280218823234. Epub 2019 Jan 23. PMID: 30674229. (PubMed)

Mba RD, Goungounga JA, Graff\'eo N, Giorgi R; CENSUR working survival group. Correcting inaccurate background mortality in excess hazard models through breakpoints. BMC Med Res Methodol. 2020 Oct 29;20(1):268. doi: 10.1186/s12874-020-01139-z. PMID: 33121436; PMCID: PMC7596976. (PubMed)

See Also

xhaz, plot.predxhaz, print.constant

Examples

# \donttest{

library("xhaz")
library("survival")
library("numDeriv")
library("survexp.fr")
library("splines")
data("dataCancer", package = "xhaz")   # load the data set in the package

fit.phBS <- xhaz(
              formula = Surv(obs_time_year, event) ~ ageCentre + immuno_trt,
              data = dataCancer, ratetable = survexp.fr,
              interval = c(0, NA, NA, max(dataCancer$obs_time_year)),
              rmap = list(age = 'age', sex = 'sexx', year = 'year_date'),
              baseline = "bsplines", pophaz = "classic")

print(fit.phBS)
# }