lmeInfo (version 0.3.2)

Fisher_info: 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)

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.

Arguments

mod

Fitted model of class lmeStruct or glsStruct.

type

Type of information matrix. One of "expected" (the default), "observed", or "average".

separate_variances

Logical indicating whether to return the Fisher information matrix for separate level-1 variance components if using varIdent function to allow for different variances per stratum. Default is FALSE.

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)