blandr.statistics: Bland-Altman statistics for R

In blandr: Bland-Altman Method Comparison

Bland-Altman statistics for R

Description

Bland-Altman analysis function for R. Package created as existing functions don't suit my needs, and don't generate 95\ for bias and limits of agreement. This base function calculates the basic statistics, and generates return values which can be used in the related blandr.display and bland.altamn.plot functions. However the return results can be used to generate a custom chart if desired.

Usage

blandr.statistics(method1, method2, sig.level = 0.95, LoA.mode = 1)

Arguments

method1	Either a formula, or a vector of numbers corresponding to the results from method 1.
method2	A vector of numbers corresponding to the results from method 2. Only needed if X is a vector.
sig.level	(Optional) Two-tailed significance level. Expressed from 0 to 1. Defaults to 0.95.
LoA.mode	(Optional) Switch to change how accurately the limits of agreement (LoA) are calculated from the bias and its standard deviation. The default is LoA.mode=1 which calculates LoA with the more accurate 1.96x multiplier. LoA.mode=2 uses the 2x multiplier which was used in the original papers. This should really be kept at default, except to double check calculations in older papers.

Value

An object of class 'blandr' is returned. This is a list with the following elements:

means	List of arithmetic mean of the two methods
differences	List of differences of the two methods
method1	Returns the 'method1' list in the data frame if further evaluation is needed
method2	Returns the 'method2' list in the data frame if further evaluation is needed
sig.level	Significance level supplied to the function
sig.level.convert.to.z	Significance level convert to Z value
bias	Bias of the two methods
biasUpperCI	Upper confidence interval of the bias (based on significance level)
biasLowerCI	Lower confidence interval of the bias (based on significance level)
biasStdDev	Standard deviation for the bias
biasSEM	Standard error for the bias
LOA_SEM	Standard error for the limits of agreement
upperLOA	Upper limit of agreement
upperLOA_upperCI	Upper confidence interval of the upper limit of agreement
upperLOA_lowerCI	Lower confidence interval of the upper limit of agreement
lowerLOA	Lower limit of agreement
lowerLOA_upperCI	Upper confidence interval of the lower limit of agreement
lowerLOA_lowerCI	Lower confidence interval of the lower limit of agreement
proportion	Differences/means*100
no.of.observations	Number of observations
regression.equation	A regression equation to help determine if there is any proportional bias
regression.fixed.slope	The slope value of the regression equation
regression.fixed.intercept	The intercept value of the regression equation

Note

The function will give similar answers when used on the original Bland-Altman PEFR data sets. They won't be exactly the same as (a) for 95\

The function depends on paired values.

It currently only can currently work out fixed bias.

Improvements for the future: proportional bias charts will need further work

Started 2015-11-14

Last update 2016-02-04

Originally designed for LAVAS and CVLA

Author(s)

Deepankar Datta [e-mail]

References

Based on: (1) Bland, J. M., & Altman, D. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet, 327(8476), 307-310. http://dx.doi.org/10.1016/S0140-6736(86)90837-8

Confidence interval work based on follow-up paper: (2) Altman, D. G., & Bland, J. M. (2002). Commentary on quantifying agreement between two methods of measurement. Clinical chemistry, 48(5), 801-802. http://www.clinchem.org/content/48/5/801.full.pdf

Examples

# Generates two random measurements
measurement1 <- rnorm(100)
measurement2 <- rnorm(100)

# Generates Bland-Altman statistics data of the two measurements
blandr.statistics( measurement1 , measurement2 )

blandr documentation built on June 22, 2024, 10:58 a.m.