FreqID_HReg {SemiCompRisks} | R Documentation |
Independent semi-competing risks data can be analyzed using hierarchical models. Markov or semi-Markov assumption can be adopted for the conditional hazard function for time to the terminal event given time to non-terminal event.
FreqID_HReg(Formula, data, model="semi-Markov", frailty = TRUE, na.action = "na.fail", subset=NULL)
Formula |
a |
data |
a data.frame in which to interpret the variables named in |
model |
a character value that specifies the type of a model based on the assumption on h_3: "semi-Markov" or "Markov". |
frailty |
a logical value to determine whether to include the subject-specific shared frailty term, γ, into the model. |
na.action |
how NAs are treated. See |
subset |
a specification of the rows to be used: defaults to all rows. See |
See BayesID_HReg
for a detailed description of the models.
FreqID_HReg
returns an object of class Freq_HReg
.
Sebastien Haneuse and Kyu Ha Lee
Maintainer: Kyu Ha Lee <klee15239@gmail.com>
Lee, K. H., Haneuse, S., Schrag, D., and Dominici, F. (2015),
Bayesian semiparametric analysis of semicompeting risks data:
investigating hospital readmission after a pancreatic cancer diagnosis, Journal of the Royal Statistical Society: Series C, 64, 2, 253-273.
Alvares, D., Haneuse, S., Lee, C., Lee, K. H. (2018+),
SemiCompRisks: an R package for independent and cluster-correlated analyses of semi-competing risks data, submitted, arXiv:1801.03567.
print.Freq_HReg
, summary.Freq_HReg
, predict.Freq_HReg
, BayesID_HReg
.
## Not run: # loading a data set data(scrData) form <- Formula(time1 + event1 | time2 + event2 ~ x1 + x2 + x3 | x1 + x2 | x1 + x2) fit_WB <- FreqID_HReg(form, data=scrData, model="semi-Markov") fit_WB summ.fit_WB <- summary(fit_WB); names(summ.fit_WB) summ.fit_WB pred_WB <- predict(fit_WB, tseq=seq(from=0, to=30, by=5)) plot(pred_WB, plot.est="Haz") plot(pred_WB, plot.est="Surv") ## End(Not run)