ccc_est {cccrm} | R Documentation |
Concordance correlation Coefficient estimation from a linear mixed model
Description
It computes the Concordance Correlation Coefficient and its asymptotic confidence interval.
Usage
ccc_est(model, D = NULL, cl = 0.95, transf = "F2", sd_est = TRUE, ...)
Arguments
model |
The lme model. |
D |
Weights vector. |
cl |
Confidence level (0.95 as a default). Bounded between 0 and 1. |
transf |
Character string. Whether to apply a transformation of the coefficient for inference. Valid options are: "F" for Fisher's Z-transformation; "F2" For Fisher's Z-transformation setting m=2 (default); "KG" Konishi-Gupta transformation; "None", no transformation is applied. See *Details* for further information. |
sd_est |
Logical. Whether to estimate the asymptotic standard deviation (defaults to TRUE) or to only report the |
... |
To pass further arguments. |
Value
A ccc
class object.
See Also
Examples
set.seed(1984)
df <- ccc_sim_data(n=50,b = c(0,1), mu = -0.25, sa = 1.5, se = 1, nrep=2)
mod <- lme_model(df,"y","id",rmet="met")
ccc_est(mod)
[Package cccrm version 3.0.5 Index]