Description Usage Arguments Author(s) References Examples
nph is used in the MRH survival model formula to denote that a variable should be modeled under the non-proportional hazards assumption.
1 | nph(x)
|
x |
x is the covariate that will be modeled under the non-proportional hazards assumption. It must be a categorical variable, although it need not be entered using the "factor" class in R. A separate hazard rate will be estimated for each group in x. |
Yolanda Hagar <yolanda.hagar@colorado.edu> and Vanja Dukic
Dukic, V., Dignam, J. (2007), Bayesian hierarchical multiresolution hazard model for the study of time-dependent failure patterns in early stage breast cancer. Bayesian Analysis. 2, 591–610.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # Examine the tongue data set (from the KMest package), and
# quantify how the rumor DNA profile (1=Aneuploid Tumor, 2=Diploid Tumor)
# affects survival time (in weeks).
data(tongue)
# Fit the MRH model, including tumor type using the
# non-proportional hazards model.
# With 16 bins (M = 4), each bin represents 25 weeks.
# Generally it is recommended to use a higher burn-in value,
# thinning value, and maximum number
# of iterations, but for illustrative purposes these values
# have been lowered.
## Not run:
fit.tongue = estimateMRH(formula = Surv(time, delta) ~
nph(type), data = tongue, M = 4,
burnIn = 200, maxIter = 2000, thin = 1,
outfolder = 'MRH_tongue_nph')
## End(Not run)
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