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Concordance correlation coefficient (CCC)

Source: R/reg_CCC.R
CCC.Rd

It estimates the Concordance Correlation Coefficient (CCC) for a continuous predicted-observed dataset.

Usage

CCC(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 CCC it is a normalized coefficient that tests general agreement. It presents both precision (r) and accuracy (Xa) components. It is positively bounded to 1. The closer to 1 the better. Values towards zero indicate low correlation between observations and predictions. Negative values would indicate a negative relationship between predicted and observed. 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)
CCC(obs = X, pred = Y)
#> $CCC
#> [1] 0.9512255
#> 
# }