Tests for Absolute Agreement

Source: R/agree_test.R

[Superseded]

Development on agree_test() is complete, and for new code we recommend switching to agreement_limit(), which is easier to use, has more features, and still under active development.

The agree_test function calculates a variety of agreement statistics. The hypothesis test of agreement is calculated by the method described by Shieh (2019). Bland-Altman limits of agreement, and confidence intervals, are also provided (Bland & Altman 1999; Bland & Altman 1986). In addition, the concordance correlation coefficient (CCC; Lin 1989) is additional part of the output.

agree_test(
  x,
  y,
  delta,
  conf.level = 0.95,
  agree.level = 0.95,
  TOST = TRUE,
  prop_bias = FALSE
)

Arguments

x

Vector with first measurement

y

Vector with second measurement

delta

The threshold below which methods agree/can be considered equivalent, can be in any units. Often referred to as the "Equivalence Bound for Agreement" or "Maximal Allowable Difference".

conf.level

the confidence level required. Default is 95%.

agree.level

the agreement level required. Default is 95%. The proportion of data that should lie between the thresholds, for 95% limits of agreement this should be 0.95.

TOST

Logical indicator (TRUE/FALSE) of whether to use two one-tailed tests for the limits of agreement. Default is TRUE.

prop_bias

Logical indicator (TRUE/FALSE) of whether proportional bias should be considered for the limits of agreement calculations.

Value

Returns single list with the results of the agreement analysis.

  • shieh_test: The TOST hypothesis test as described by Shieh.

  • ccc.xy: Lin's concordance correlation coefficient and confidence intervals.

  • s.shift: Scale shift from x to y.

  • l.shift: Location shift from x to y.

  • bias: a bias correction factor that measures how far the best-fit line deviates from a line at 45 degrees. No deviation from the 45 degree line occurs when bias = 1. See Lin 1989, page 258.

  • loa: Data frame containing the limits of agreement calculations

  • h0_test: Decision from hypothesis test.

  • call: the matched call

References

Shieh (2019). Assessing Agreement Between Two Methods of Quantitative Measurements: Exact Test Procedure and Sample Size Calculation, Statistics in Biopharmaceutical Research, doi:10.1080/19466315.2019.1677495

Bland, J. M., & Altman, D. G. (1999). Measuring agreement in method comparison studies. Statistical methods in medical research, 8(2), 135-160.

Bland, J. M., & Altman, D. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The lancet, 327(8476), 307-310.

Lawrence, I., & Lin, K. (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics, 255-268.

Examples

data('reps')
agree_test(x=reps$x, y=reps$y, delta = 2)
#> Warning: `agree_test()` was deprecated in SimplyAgree 0.2.0.
#> ℹ Please use `agreement_limit()` instead.
#> Limit of Agreement = 95%
#> 
#> ###- Shieh Results -###
#> Exact 90% C.I.  [-2.6418, 3.5184]
#> Hypothesis Test: don't reject h0
#> 
#> ###- Bland-Altman Limits of Agreement (LoA) -###
#>           Estimate Lower CI Upper CI CI Level
#> Bias        0.4383  -0.1669    1.044     0.95
#> Lower LoA  -1.9470  -2.8162   -1.078     0.90
#> Upper LoA   2.8237   1.9545    3.693     0.90
#> 
#> ###- Concordance Correlation Coefficient (CCC) -###
#> CCC: 0.4791, 95% C.I. [0.1276, 0.7237]