ClinicalUtilityRecal (version 0.1.0)

cvWtTuning: Cross-validation for Selecting Weight Tuning Parameter

Description

Calibration weights require specification of tuning parameter $delta$ or $lambda$. This function uses K-fold cross-validation to select tuning parameter used for calibration weights, with standardized net benfeit (sNB) as objective function. Either one of $delta$ or $lambda$ must be specificed. The sequence of tuning parameters can be obtained from the RAWgrid function.

Usage

cvWtTuning(p,y,r,rl,ru,kFold=5,cvParm,tuneSeq,cv.seed=1111)

Arguments

y

Vector of binary outcomes, with 1 indicating event (cases) and 0 indicating no event (controls)

p

Vector of risk score values

r

Clinically relevant risk threshold

rl

Lower bound of clinically relevant region

ru

Upper bound of clinically relevant region

kFold

Number of folds for cross-validation

cvParm

Parameter to be selected via cross-validation. Can be either $delta$ the weight assigned to observations outside the clinically relevant region [R_l,R_u], or the $lambda$ tuning parameter controlling exponential decay within the clinically relevant region [R_l,R_u]

tuneSeq

Sequence of values of tuning parameters to perform cross-validation over

cv.seed

Intial seed set for random splitting of data into K folds

Value

cv.res

Matrix containing sequence of tuning parameters and corresponding cross-validation sNB

cv.param

Value of tuning parameter selected via cross validation

cv.full

Matrix of cross-validation results for all folds

References

Mishra, A. (2019). Methods for Risk Markers that Incorporate Clinical Utility (Doctoral dissertation). (Available Upon Request)

See Also

calWt, RAWgrid, nb, cvRepWtTuning