RC_ExReliab: Unified Regression Calibration Wrapper (External Reliability...

In RegCalReliab: Regression Calibration Using Reliability Studies

Unified Regression Calibration Wrapper (External Reliability Study)

Description

A single formula interface for regression calibration in external reliability studies. The user simply specifies 'link = "linear"', '"logistic"', or '"log"', and the wrapper selects the appropriate model: * '"linear"' → Gaussian (identity link) * '"logistic"' → Binomial (logit link) * '"log"' → Poisson (log link)

Usage

RC_ExReliab(
  formula,
  main_data,
  rep_data,
  link = c("linear", "logistic", "log"),
  return_details = FALSE
)

Arguments

formula	A formula or character string such as 'Y ~ sbp(sbp2, sbp3) + chol(chol2, chol3) + age + weight'. Terms of the form 'var(rep1, rep2, ...)' are treated as error-prone exposures with replicates in 'rep_data'; other terms are treated as covariates W.
main_data	Data frame holding the outcome, error-prone exposures, and covariates.
rep_data	Data frame holding replicate columns referenced in 'formula'.
link	Character; one of '"linear"', '"logistic"', or '"log"'.
return_details	Logical; if 'TRUE', return parsed, prepared, and RC internals.

Value

A list with: * 'uncorrected': naive regression estimates * 'corrected' : sandwich-corrected regression calibration estimates * optional 'details' if 'return_details = TRUE'

Examples

library(mgcv)
set.seed(123)
add_err <- function(v, sd = sqrt(0.4)) v + rnorm(length(v), 0, sd)

## --- Example 1: External 1Z 0W ---
x <- rnorm(3000)
z.main <- x[1:1500] + rnorm(1500, 0, sqrt(0.4))
z_rep <- rbind(
  cbind(add_err(x[1501:2000]), add_err(x[1501:2000]), NA, NA),
  cbind(add_err(x[2001:2400]), add_err(x[2001:2400]), add_err(x[2001:2400]), NA),
  cbind(add_err(x[2401:3000]), add_err(x[2401:3000]),
        add_err(x[2401:3000]), add_err(x[2401:3000]))
)
colnames(z_rep) <- paste0("z_", 1:4)
Y <- rbinom(1500, 1, plogis(-2.3 + log(1.5) * x[1:1500]))
main_data <- data.frame(Y = Y, z = z.main)
rep_data  <- data.frame(z_rep, check.names = FALSE)
res1 <- RC_ExReliab(Y ~ z(z_1, z_2, z_3, z_4), main_data, rep_data, link = "logistic")
res1$corrected

## --- Example 2: External 1Z 1W ---
x <- rnorm(3000)
W_main <- rnorm(1500)
W_rep  <- rnorm(1500)
z.main <- x[1:1500] + rnorm(1500, 0, sqrt(0.4))
z_rep <- rbind(
  cbind(add_err(x[1501:2000]), add_err(x[1501:2000]), NA, NA),
  cbind(add_err(x[2001:2400]), add_err(x[2001:2400]), add_err(x[2001:2400]), NA),
  cbind(add_err(x[2401:3000]), add_err(x[2401:3000]),
        add_err(x[2401:3000]), add_err(x[2401:3000]))
)
colnames(z_rep) <- paste0("z_", 1:4)
Y <- rbinom(1500, 1, plogis(-2.3 + log(1.5) * x[1:1500] + 0.5 * W_main))
main_data <- data.frame(Y = Y, z = z.main, W = W_main)
rep_data  <- data.frame(z_rep, W = W_rep, check.names = FALSE)
res2 <- RC_ExReliab(Y ~ z(z_1, z_2, z_3, z_4) + W, main_data, rep_data, link = "logistic")
res2$corrected

## --- Example 3: External 2Z 0W ---
x <- mgcv::rmvn(3000, c(0, 0), matrix(c(1, 0.3, 0.3, 1), 2))
z.main <- x[1:1500, ] + matrix(rnorm(1500 * 2, 0, sqrt(0.4)), 1500, 2)
colnames(z.main) <- c("z1", "z2")
z1_rep <- rbind(
  cbind(add_err(x[1501:2000, 1]), add_err(x[1501:2000, 1]), NA, NA),
  cbind(add_err(x[2001:2400, 1]), add_err(x[2001:2400, 1]), add_err(x[2001:2400, 1]), NA),
  cbind(add_err(x[2401:3000, 1]), add_err(x[2401:3000, 1]),
        add_err(x[2401:3000, 1]), add_err(x[2401:3000, 1]))
)
colnames(z1_rep) <- paste0("z1_", 1:4)
z2_rep <- rbind(
  cbind(add_err(x[1501:2000, 2]), add_err(x[1501:2000, 2]), NA, NA),
  cbind(add_err(x[2001:2400, 2]), add_err(x[2001:2400, 2]), add_err(x[2001:2400, 2]), NA),
  cbind(add_err(x[2401:3000, 2]), add_err(x[2401:3000, 2]),
        add_err(x[2401:3000, 2]), add_err(x[2401:3000, 2]))
)
colnames(z2_rep) <- paste0("z2_", 1:4)
Y <- rbinom(1500, 1, plogis(-2.3 + log(1.5) * rowSums(x[1:1500, ])))
main_data <- data.frame(Y = Y, z1 = z.main[, 1], z2 = z.main[, 2])
rep_data  <- data.frame(z1_rep, z2_rep, check.names = FALSE)
res3 <- RC_ExReliab(
  Y ~ z1(z1_1, z1_2, z1_3, z1_4) + z2(z2_1, z2_2, z2_3, z2_4),
  main_data, rep_data, link = "logistic"
)
res3$corrected

RegCalReliab documentation built on Nov. 6, 2025, 1:18 a.m.