pIndexControl: Auxiliary function for pIndex fitting

In bhm: Biomarker Threshold Models

Auxiliary function for pIndex fitting

Description

Auxiliary function for pIndex fitting. Typically only used internally by 'pIndexFit', but may be used to construct a control argument to either function.

Usage

  pIndexControl(method = c("Efron", "Elc", "Elw", "Pic"), 
                model = c("default", "local", "threshold"), 
	        ci = c("Bootstrap", "Jackknife"), weights = NULL, 
		kernel = NULL, h = 0.1, w  = seq(0.05, 0.95, 0.05), 
		alpha = 0.05, B = 0, pct = 0.5, tau=NULL) 

Arguments

method	choose either ‘Efron’ for Efron method, ‘Elc’ for conditional empirical likelihood, ‘Elw’ for weighted empirical likelihood method, and ‘Pic’ for piecewise exponential distribution. The default value is ‘Efron’
model	‘default’ for default pIndex model, ‘local’ for kernel method, ‘threshold’ for threshold method
ci	Method to construct confidence interval, ‘Bootstrap’ for Bootstrap method and ‘Jackknife’ for Jackknife method
weights	case weight
kernel	kernel funtion types, including "gaussian", "epanechnikov", "rectangular", "triangular", "biweiht", "cosine", "optcosine". The default value is ‘gaussian’
h	bandwidth, defaul is 0.1
w	percentile of biomarker value for local fit
B	number of Bootstrap sample
alpha	significance level (e.g. alpha=0.05)
pct	Percentile of threshold (i.e. the cut point), default is 0.5
tau	maximum time tau to be used for pIndex

Details

Control is used in model fitting of ‘pIndex’.

Value

This function checks the internal consisitency and returns a list of value as inputed to control model fit of pIndex.

Note

Based on code from Bingshu E. Chen.

Author(s)

Bingshu E. Chen

See Also

bhm, pIndex

Examples

## To calculate the probability index for a biomarker with conditional empirical likelihood method, 
## and the corresponding 90 percent CI using Bootstrap method with 10000 bootstrap sample

ctl = pIndexControl(method = 'Elc', ci = 'Bootstrap', B = 10000, alpha = 0.1)

##
## then fit the following model
##
#  fit = pIndex(y~x1 + x2, family = 'surv', control = ctl)
##

bhm documentation built on June 8, 2025, 1:45 p.m.