Fisher_info: Calculate expected, observed, or average Fisher information...

In lmeInfo: Information Matrices for 'lmeStruct' and 'glsStruct' Objects

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 "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.

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)

lmeInfo documentation built on April 17, 2023, 9:08 a.m.