View source: R/anova.mexhazLT.R
anova.mexhazLT | R Documentation |
This function compute an analysis of deviance table for two excess hazard models fitted using xhaz R package.
## S3 method for class 'mexhazLT'
anova(object, ..., test = "LRT")
object |
an object of class mexhazLT |
... |
an object of class mexhazLT |
test |
a character string. The appropriate test is a likelihood-ratio test, all other choices result in Not yet implemented test. |
An object of class anova
inheriting from class matrix
.
The different columns contain respectively the degrees of freedom and the
log-likelihood values of the two nested models, the degree of freedom of the
chi-square statistic, the chi-square statistic and the p-value of the
likelihood ratio test.
As expected, the comparison between two or more models by anova or more excess hazard models will only be valid if they are fitted to the same dataset, and if the compared models are nested. This may be a problem if there are missing values.
Juste Goungounga, Hadrien Charvat, Robert Darlin Mba, Nathalie Graff\'eo and Roch Giorgi
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)
Goungounga, JA, Graff\'eo N, Charvat H, Giorgi R. “Correcting for heterogeneity and non-comparability bias in multicenter clinical trials with a rescaled random-effect excess hazard model.” Biometrical journal. Biometrische Zeitschrift vol. 65,4 (2023): e2100210. doi:10.1002/bimj.202100210.PMID: 36890623; (PubMed)
xhaz
, mexhazLT
, AIC.mexhazLT
# load the data set in the package
library("survival")
library("numDeriv")
library("survexp.fr")
breast$sexe <- "female"
fit.haz <- exphaz(
formula = Surv(temps, statut) ~ 1,
data = breast, ratetable = survexp.us,
only_ehazard = FALSE,
rmap = list(age = 'age', sex = 'sexe', year = 'date'))
breast$expected <- fit.haz$ehazard
breast$expectedCum <- fit.haz$ehazardInt
mod.bs3 <- mexhazLT(formula = Surv(temps, statut) ~ agecr + armt,
data = breast,
ratetable = survexp.us, degree = 3,
knots=quantile(breast[breast$statut==1,]$temps, probs=c(1:2/3)),
expected = "expected",expectedCum = "expectedCum",
base = "exp.bs", pophaz = "classic", random ="hosp")
mod.bs3
mod.bs4 <- mexhazLT(formula = Surv(temps, statut) ~ agecr + armt,
data = breast,
ratetable = survexp.us, degree = 3,
knots=quantile(breast[breast$statut==1,]$temps, probs=c(1:2/3)),
expected = "expected",expectedCum = "expectedCum",
base = "exp.bs", pophaz = "rescaled", random = "hosp")
mod.bs4
anova(mod.bs3, mod.bs4)
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