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It estimates the Xa component for the calculation of the Concordance Correlation Coefficient (CCC) following Lin (1989).

Usage

Xa(data = NULL, obs, pred, tidy = FALSE, na.rm = TRUE)

Arguments

data

(Optional) argument to call an existing data frame containing the data.

obs

Vector with observed values (numeric).

pred

Vector with predicted values (numeric).

tidy

Logical operator (TRUE/FALSE) to decide the type of return. TRUE returns a data.frame, FALSE returns a list; Default : FALSE.

na.rm

Logic argument to remove rows with missing values (NA). Default is na.rm = TRUE.

Value

an object of class numeric within a list (if tidy = FALSE) or within a data frame (if tidy = TRUE).

Details

The Xa measures accuracy of prediction. It goes from 0 (completely inaccurate) to 1 (perfectly accurate). It is used to adjust the precision measured by the correlation coefficient (r) in order to evaluate agreement through the CCC. For the formula and more details, see online-documentation

References

Lin (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics 45 (1), 255–268. doi:10.2307/2532051

Examples

# \donttest{
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- X + rnorm(n=100, mean = 0, sd = 3)
Xa(obs = X, pred = Y)
#> $Xa
#> [1] 0.9987515
#> 
# }