Passing-Bablok Regression for Method Comparison

Performs Passing-Bablok regression, a non-parametric method for comparing two analytical methods. This is robust to outliers and does not require normal distribution of residuals.

Usage

measure_passing_bablok(
  data,
  method1_col,
  method2_col,
  conf_level = 0.95,
  alpha = 0.05
)

Arguments

data

A data frame containing paired measurements.

method1_col

Name of column for method 1 (reference/comparator).

method2_col

Name of column for method 2 (test method).

conf_level

Confidence level for intervals. Default is 0.95.

alpha

Significance level for CUSUM linearity test. Default is 0.05.

Value

A measure_passing_bablok object containing:

• coefficients: Tibble with intercept and slope estimates and CIs

• linearity: CUSUM test results for linearity assumption

• statistics: Summary statistics

Details

Method

Passing-Bablok regression:

1. Calculates slopes between all pairs of points

2. Uses median slope as the estimate (robust to outliers)

3. Calculates intercept from median slope

4. Uses non-parametric confidence intervals

CUSUM Linearity Test

Tests the assumption of linear relationship. If significant (p < alpha), the linear model may not be appropriate.

Interpretation

For equivalent methods:

• 95% CI for slope includes 1

• 95% CI for intercept includes 0

Requirements

This function requires the mcr package. Install with: install.packages("mcr")

See also

measure_bland_altman(), measure_deming_regression()

Other method-comparison: measure_bland_altman(), measure_deming_regression(), measure_proficiency_score()

Examples

if (FALSE) { # \dontrun{
# Requires mcr package
data <- data.frame(
  reference = c(5.2, 10.5, 15.8, 25.3, 50.1, 75.4, 100.2),
  new_method = c(5.1, 10.8, 16.2, 25.9, 49.8, 76.1, 101.3)
)

result <- measure_passing_bablok(
  data,
  method1_col = "reference",
  method2_col = "new_method"
)

print(result)
} # }