joint_test: Joint Confidence Region Test for Method Agreement

In SimplyAgree: Flexible and Robust Agreement and Reliability Analyses

Joint Confidence Region Test for Method Agreement

Description

Tests whether the estimated intercept and slope jointly fall within a confidence region around specified ideal values (typically intercept=0 and slope=1 for method comparison studies).

Usage

joint_test(object, ...)

## S3 method for class 'simple_eiv'
joint_test(
  object,
  ideal_intercept = 0,
  ideal_slope = 1,
  conf.level = 0.95,
  ...
)

Arguments

object	A simple_eiv object from dem_reg() or pb_reg().
...	Additional arguments (currently unused).
ideal_intercept	The hypothesized intercept value (default: 0).
ideal_slope	The hypothesized slope value (default: 1).
conf.level	Confidence level for the test (default: 0.95).

Details

The test computes the Mahalanobis distance between the estimated coefficients and the hypothesized values using the variance-covariance matrix of the estimates. Under the null hypothesis, this distance follows a chi-squared distribution with 2 degrees of freedom.

For Deming regression, the variance-covariance matrix is computed via jackknife. For Passing-Bablok regression, bootstrap resampling must have been performed (i.e., boot_ci = TRUE in the original call).

Value

An object of class htest containing:

statistic

The Mahalanobis distance (chi-squared distributed with df=2).

parameter

Degrees of freedom (always 2).

p.value

The p-value for the test.

conf.int

The confidence level used.

estimate

Named vector of estimated intercept and slope.

null.value

Named vector of hypothesized intercept and slope.

alternative

Description of the alternative hypothesis.

method

Description of the test.

data.name

Name of the input object.

SimplyAgree documentation built on Jan. 22, 2026, 1:08 a.m.