Fisher_info {lmeInfo} | R Documentation |
Calculate expected, observed, or average Fisher information matrix
Description
Calculates the expected, observed, or average Fisher information matrix from a fitted linear mixed effects model (lmeStruct object) or generalized least squares model (glsStruct object).
Usage
Fisher_info(mod, type = "expected", separate_variances = FALSE)
Arguments
mod |
Fitted model of class lmeStruct or glsStruct. |
type |
Type of information matrix. One of |
separate_variances |
Logical indicating whether to return the Fisher
information matrix for separate level-1 variance components if using
|
Value
Information matrix corresponding to variance component parameters of
mod
.
If separate_variances = TRUE
and if weights = varIdent(form =
~ 1 | Stratum)
is specified in the model fitting, the Fisher information
matrix for separate level-1 variance estimates will be returned. If
separate_variances = TRUE
but if the weighting structure is not
specified with varIdent
, or if separate_variances = FALSE
,
then the Fisher information matrix for the default variance components will
be returned.
Examples
library(nlme)
data(Bryant2016)
Bryant2016_RML <- lme(fixed = outcome ~ treatment,
random = ~ 1 | school/case,
correlation = corAR1(0, ~ session | school/case),
data = Bryant2016)
Fisher_info(Bryant2016_RML, type = "expected")
Fisher_info(Bryant2016_RML, type = "average")
Bryant2016_RML2 <- lme(fixed = outcome ~ treatment,
random = ~ 1 | school/case,
correlation = corAR1(0, ~ session | school/case),
weights = varIdent(form = ~ 1 | treatment),
data = Bryant2016)
Fisher_info(Bryant2016_RML2, separate_variances = TRUE)