coef.lmm: Extract Coefficients From a Linear Mixed Model

In bozenne/repeated: Repeated Measurement Models for Discrete Times

Extract Coefficients From a Linear Mixed Model

Description

Extract estimated parameters from a linear mixed model.

Usage

## S3 method for class 'lmm'
coef(
  object,
  effects = NULL,
  p = NULL,
  transform.sigma = NULL,
  transform.k = NULL,
  transform.rho = "none",
  transform.names = TRUE,
  simplify = TRUE,
  ...
)

Arguments

object	a lmm object.
effects	[character] Should all coefficients be output ("all"), or only coefficients relative to the mean ("mean" or "fixed"), or only coefficients relative to the variance structure ("variance"), or only coefficients relative to the correlation structure ("correlation"). or the random effects ("ranef") when using a random effect model.
p	[numeric vector] value of the model coefficients to be used. Only relevant if differs from the fitted values.
transform.sigma	[character] Transformation used on the variance coefficient for the reference level. One of "none", "log", "square", "logsquare" - see detail##' @param transform.k [character] Transformation used on the variance coefficients relative to the other levels. One of "none", "log", "square", "logsquare", "sd", "logsd", "var", "logvar" - see details.
transform.rho	[character] Transformation used on the correlation coefficients. One of "none", "atanh", "cov" - see details.
transform.names	[logical] Should the name of the coefficients be updated to reflect the transformation that has been used?
simplify	[logical] Omit from the output the attribute containing the type of each parameter (mu/sigma/k/rho) and the corresponding variance parameters (sigma/k.x/k.y).
...	Not used. For compatibility with the generic method.

Details

transform.sigma:

• "none" ouput residual standard error.

• "log" ouput log-transformed residual standard error.

• "square" ouput residual variance.

• "logsquare" ouput log-transformed residual variance.

transform.k:

• "none" ouput ratio between the residual standard error of the current level and the reference level.

• "log" ouput log-transformed ratio between the residual standard errors.

• "square" ouput ratio between the residual variances.

• "logsquare" ouput log-transformed ratio between the residual variances.

• "sd" ouput residual standard error of the current level.

• "logsd" ouput residual log-transformed standard error of the current level.

• "var" ouput residual variance of the current level.

• "logvar" ouput residual log-transformed variance of the current level.

transform.rho:

• "none" ouput correlation coefficient.

• "atanh" ouput correlation coefficient after tangent hyperbolic transformation.

• "cov" ouput covariance coefficient.

Value

A vector with the value of the model coefficients.
When using simplify=FALSE the character strings in attribute "type" refer to:

• "mu": mean parameters.

• "sigma": standard deviation parameters,

• "k": ratio between standard deviation,

• "rho": correlation parameter

The character strings in attribute "sigma" refer, for each parameter, to a possible corresponding standard deviation parameter. Those in attribute "k.x" and "k.y" refer to the ratio parameter. NA indicates no corresponding standard deviation or ratio parameter.

See Also

confint.lmm or model.tables.lmm for a data.frame containing estimates with their uncertainty.

Examples

## simulate data in the long format
set.seed(10)
dL <- sampleRem(100, n.times = 3, format = "long")

## fit linear mixed model
eUN.lmm <- lmm(Y ~ X1 + X2 + X5, repetition = ~visit|id, structure = "UN", data = dL, df = FALSE)

## output coefficients
coef(eUN.lmm)
coef(eUN.lmm, effects = "variance", transform.k = "sd")
coef(eUN.lmm, effects = "all", simplify = FALSE)

bozenne/repeated documentation built on July 16, 2025, 11:16 p.m.