print.bsplines {xhaz}

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 class 'bsplines'
print(x, digits = max(options()$digits - 4, 3), ...)

Arguments

x

an object of class bsplines

digits

minimal number of significant digits.

...

additionnal parameters which can be used in the print function

Value

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

References

Goungounga JA, Touraine C, Grafféo 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, Grafféo 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, Grafféo 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

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)