nph: INTERNAL FUNCTION NEEDED FOR NON-PROPORTIONAL HAZARDS MODELS.

Description Usage Arguments Author(s) References Examples

Description

nph is used in the MRH survival model formula to denote that a variable should be modeled under the non-proportional hazards assumption.

Usage

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nph(x)

Arguments

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.

Author(s)

Yolanda Hagar <yolanda.hagar@colorado.edu> and Vanja Dukic

References

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.

Examples

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# 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)

MRH documentation built on May 2, 2019, 11:10 a.m.