snsp2mp {SenSpe} | R Documentation |
Two-biomarker paired comparison in specificity (or sensitivity) at a controlled sensitivity (or specificity) level
Description
Point estimation and exact bootstrap-based inference
Usage
snsp2mp(mk, n1, s0, covp=0.95, fixsens=TRUE, lbmdis=TRUE)
Arguments
mk |
Each of two rows corresponds to a biomarker, cases followed by controls. |
n1 |
case size. |
s0 |
controlled level of sensitivity or specificity. |
covp |
norminal level of confidence intervals. |
fixsens |
fixing sensitivity if True, and specificity otherwise. |
lbmdis |
larger value of a biomarker is more associated with cases if True, and controls otherwise. |
Value
diff |
diff[1]: difference of empirical point estimates; hss[2]: difference of oscillating bias-corrected estimates. |
btmn |
bootstrap mean of the empirical difference. |
btva |
exact bootstrap variance estimate for diff[1]. |
btdist |
exact bootstrap probability mass function at (-n0:n0)/n0 with n0 being the size of controls if sensitivity is controlled, or at (-n1:n1)/n1 otherwise. |
wald_ci |
wald_ci[1,]: Wald confidence interval using diff[1]; wald_ci[2,]: Wald confidence interval using diff[2]. |
pct_ci |
percentile confidence interval. |
scr_ci |
scr_ci[1,]: score confidence interval using diff[1]; scr_ci[2,]: score confidence interval using diff[2]. |
zq_ci |
extension of the BTII in Zhou and Qin (2005, Statistics in Medicine 24, pp 465–477). |
Author(s)
Yijian Huang
References
Huang, Y., Parakati, I., Patil, D. H.,and Sanda, M. G. (2023). Interval estimation for operating characteristic of continuous biomarkers with controlled sensitivity or specificity, Statistica Sinica 33, 193–214.
Examples
## simulate paired biomarkers X and Y, with correlation 0.5, 100 cases and 100 controls
n1 <- 100
n0 <- 100
rho <- 0.5
set.seed(1234)
mkx <- rnorm(n1+n0,0,1)
mky <- rho*mkx + sqrt(1-rho^2)*rnorm(n1+n0,0,1)
mkx <- mkx + c(rep(2,n1),rep(0,n0))
mky <- mky + c(rep(1,n1),rep(0,n0))
mk <- rbind(mkx,mky)
## compare specificity at controlled 0.95 sensitivity
est <- snsp2mp(mk, 100, 0.95)