Print Method for Adjusted Contingency Tables

Prints the estimated contingency table (corrected for linkage error) and a summary of the adjustment parameters used by the mixture model.

Usage

# S3 method for class 'ctableMixture'
print(x, digits = 3, ...)

Arguments

x

An object of class ctableMixture.

digits

Integer; the number of significant digits to use when printing numeric values. Defaults to 3.

...

Additional arguments passed to print.default.

Value

The argument x, invisibly.

See also

plctable, ctableMixture

Examples

set.seed(125)
n <- 300

# 1. Simulate true categorical data with dependency
exposure <- sample(c("low", "high"), n, replace = TRUE)

# Induce dependency - High exposure -> higher disease probability
prob_disease <- ifelse(exposure == "high", 0.7, 0.3)
true_disease <- ifelse(runif(n) < prob_disease, "yes", "no")

# 2. Induce 15% linkage error
mis_idx <- sample(1:n, size = floor(0.15 * n))
obs_disease <- true_disease
obs_disease[mis_idx] <- sample(obs_disease[mis_idx])

linked_df <- data.frame(exposure = exposure, disease = obs_disease)

# 3. Fit the adjusted contingency table model
adj <- adjMixture(linked.data = linked_df, m.rate = 0.15)
fit <- plctable(~ exposure + disease, adjustment = adj)

# 4. Explicitly call the print method
print(fit)
#> 
#> Call:
#> plctable(formula = ~exposure + disease, adjustment = adj)
#> 
#> --- Adjusted Contingency Table (Estimated Correct Counts) ---
#>         disease
#> exposure      no     yes
#>     high  45.196  95.848
#>     low  118.699  40.257
#> 
#> --- Linkage Error Adjustment ---
#> Assumed Mismatch Rate (alpha): 0.15 
#> Status: Converged in 1 iterations.