desc.stat {BivRegBLS}

Descriptive statistics in method comparison studies

Description

Calculate several descriptive statistics in method comparison studies per device (X and Y) and per type of samples.

Usage

desc.stat(data = NULL, xcol = 1, ycol = 2, IDcol = NULL)

Arguments

data

a data set (data frame or matrix).

xcol

a numeric vector to specify the X column(s) or a character vector with the column names.

ycol

a numeric vector to specify the Y column(s) or a character vector with the column names.

IDcol

a numeric or character variable to specify the column with the different IDs or type of samples.

Details

If IDcol is null (as by default), the descriptive statistics are calculated for X and Y. Otherwise, the descriptive statistics are calculated for X and Y for each type of sample (each ID) (with a maximum of 30 different IDs). This information is also used to differentiate the observations on a raw plot when the function raw.plot is used. In presence of missing values on X or Y and non-replicates, the rows with missing values are removed. In presence of replicates, the rows with missing values are removed if all Xi or all Yi are missing.
The results (Xij, Yik, Xi, Yi, nxi, nyi, variances_x, variances_y) are reordered according to the increasing values of Xi (the X mean values).

Value

A list including the following elements:

Xij

a table with the (replicated) X measurements (replicates are in columns).

Yik

a table with the (replicated) Y measurements (replicates are in columns).

Xi

a vector with the means of the X measurements.

Yi

a vector with the means of the Y measurements.

IDs

a vector with the different IDs.

nxi

a vector with the number of X replicates per sample (patient).

nyi

a vector with the number of Y replicates per sample (patient).

variances_x

a vector with the variances calculated on the X replicates per sample (patient).

variances_y

a vector with the variances calculated on the Y replicates per sample (patient).

Order.Xi

a vector with the order of the means of the X replicates.

statistics

a table with different descriptive statistics per type of sample (rows): the number of sample (patient), the number of replicates in X and Y, the degrees of freedom of the measurement error variances in X and Y, the mean, the sum of squares (Sxx and Syy), the cross-product (Sxy), the variance, minimum, 1st quartile, median, 3rd quartile, maximum for X and Y, and the Pearson correlation coefficient and its square.

Author(s)

Bernard G FRANCQ

References

Francq BG, Govaerts BB. How to regress and predict in a Bland-Altman plot? Review and contribution based on tolerance intervals and correlated-errors-in-variables models. Statistics in Medicine, 2016; 35:2328-2358.
Francq BG. Errors-in-variables regressions to assess equivalence in method comparison studies. Ph.D. Thesis, Universite Catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial science, Louvain-la-Neuve, Belgium, 2013.

See Also

lambdas, raw.plot

Examples

library(BivRegBLS)
data(Aromatics)
res=desc.stat(data=Aromatics,xcol=3,ycol=4,IDcol=2)