pIndexControl | R Documentation |
Auxiliary function for pIndex
fitting.
Typically only used internally by 'pIndexFit', but may be used to construct a control argument to either function.
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)
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 |
Control is used in model fitting of ‘pIndex’.
This function checks the internal consisitency and returns a list of value as inputed to control model fit of pIndex.
Based on code from Bingshu E. Chen.
Bingshu E. Chen
bhm, pIndex
## 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) ##
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