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Fit Cox Proportional Hazards Models with Linkage Error Adjustment

Source: R/02_plcoxph.R
plcoxph.Rd

plcoxph fits Cox proportional hazards models to linked data, adjusting for potential mismatch errors. It serves as a wrapper around the internal fitcoxph function, for compatibility with the coxph syntax.

Usage

plcoxph(
  formula,
  adjustment,
  subset,
  na.action,
  model = TRUE,
  x = FALSE,
  y = FALSE,
  control = list(),
  ...
)

Arguments

formula

A formula object, with the response on the left of a ~ operator, and the terms on the right. The response must be a survival object as returned by the Surv function.

adjustment

An object inheriting from class "adjustment", or a list containing the necessary parameter specifications.

subset

An optional vector specifying a subset of observations.

na.action

A function for handling NAs.

model

Logical; if TRUE, the model frame is returned.

x, y

Logical; if TRUE, the model matrix (x) and response (y) are returned. Defaults are FALSE and FALSE.

control

A list of parameters for controlling the linkage error adjustment process.

...

Additional arguments passed to the internal function.

Value

An object representing the fitted model. The specific class and structure of the returned object depend directly on the adjustment method provided:

  • If adjustment is of class adjELE, returns an object of class coxphELE.

  • If adjustment is of class adjMixture, returns an object of class coxphMixture.

See also

adjELE, adjMixture, coxphELE, coxphMixture

Examples

library(survival)
set.seed(101)
n <- 250

# Simulate true survival data
x <- rnorm(n)
true_hazard <- exp(0.5 * x)
true_time <- rexp(n, true_hazard)
true_status <- rbinom(n, 1, 0.8)

# Induce linkage mismatch errors
match_score <- rbeta(n, 5, 1)
is_mismatch <- rbinom(n, 1, 1 - match_score)

obs_time <- true_time
obs_status <- true_status
mismatch_idx <- which(is_mismatch == 1)

# Shuffle time and status together for mismatched records
shuffled_idx <- sample(mismatch_idx)
obs_time[mismatch_idx] <- obs_time[shuffled_idx]
obs_status[mismatch_idx] <- obs_status[shuffled_idx]

linked_data <- data.frame(time = obs_time, status = obs_status, x = x, match_score)

# Specify the Adjustment Method
adj <- adjMixture(
  linked.data = linked_data,
  m.formula = ~ match_score
)

# Fit the Adjusted Cox Proportional Hazards Model
fit <- plcoxph(
  Surv(time, status) ~ x,
  adjustment = adj,
  control = list(max.iter = 50)
)