NAPrior (version 0.2.0)

tune_param_eNAP: Calibrate (a, b) for eNAP prior

Description

Calibrates the tuning parameters \((a,b)\) of the elastic NAP prior. This function supports both the one external trial setting and multiple external trials setting:

• Single external trial provide y_C2C1 and s_C2C1 as scalars.

• Multiple external trials provide y_C2C1 and s_C2C1 as vectors of same lengths. by default the cross-trial variance will be automatically calculated by REML, otherwise please provide the cross-trial variance as input parameter: sigma2_hat

Usage

tune_param_eNAP(
  s_EC2,
  s_EC1,
  s_C2C1,
  tau0 = 1000,
  delta = 0.5,
  t1 = 0.999,
  t0 = 0.05,
  clip_a = c(-5, -0.5),
  clip_b = c(1e-05, 50),
  exact = FALSE,
  y_EC1 = -0.5,
  y_C2C1 = -0.5,
  mu0 = 0,
  sigma2_hat = NULL,
  verbose = FALSE
)

Value

list with a, b, mode ("FE" or "RE"), and simple check summary.

Arguments

s_EC2, s_EC1, s_C2C1

Sampling variances for post-SoC change period (E vs. C2), pre-SoC change period of current trial (E vs. C1 trial) and external trial (C2 vs. C1 trial)

delta

Positive scalar; Clinically significant difference on the log-HR scale such that direct and indirect evidence should be considered as strongly inconsistent.

t1, t0

Positive scalar; Calibration targets at consisntency and strongly inconsistency: \(w'(0)=t1\) (near 1; default 0.99), \(w'(\delta)=t0\) (near 0; default 0.05).

clip_a, clip_b

Numeric Vector of Legnth 2: Minimum and maximum caps for tuning parameters (a,b), by default clip_a=(-5,0.5) and clip_b=(0,50)

exact

Logical (TRUE/FALSE); If TRUE, require the exact solution for parameter (a,b), which further requires more parameters input

y_EC1, y_C2C1

Log-HR for pre-SoC change period and external trial, required only if exact=TRUE

mu0, tau0

Mean and variance for the vague component, by default mu0=0 and tau0=1000.

sigma2_hat

Positive scalar, required only for multiple external trials setting, leave blank if use default REML estimate, otherwise provide user-specified value

verbose

Logical; print diagnostics.

Details

Calibration procedure:

• Consistency case (\(Z = 0\)). Enforce near-full borrowing at exact consistency by solving \(w'(Z = 0) = t_1\) for \(a\).

• Strong inconsistency case (\(Z(\delta)=\frac{|\delta|}{\sqrt{s_{E,C_2}+s_{E,C_1}+s_{C_2,C_1}}}).\) Enforce minimal borrowing at a clinically significant difference by targeting the updated weight \(w'(Z(\delta)) = t_0\), with calibrated a from step 1, solve for \(b\).

For further details, see the original NAP paper by Zhang and et al. (manuscript).

Examples

s_EC2 <- 0.2^2; s_EC1 <- 0.18^2; s_C2C1 <- 0.18^2
tau0 <- 1000

# One external trial setting
tune_param_eNAP(
  s_EC2,s_EC1,s_C2C1, tau0=1000,
  delta=0.5, t1 = 0.999, t0 = 0.05)

# Multiple external trials setting
s_C2C1=c(0.19^2,0.18^2,0.20^2)
y_C2C1=c(-0.5,-0.45,-0.6)
tune_param_eNAP(
  s_EC2,s_EC1,s_C2C1, tau0=10,
  delta=0.5, t1 = 0.999, t0 = 0.05,
  exact=TRUE,y_EC1=-0.8,y_C2C1=y_C2C1)