modify: Modifying model parameters.

In pitakakariki/simr: Power Analysis for Generalised Linear Mixed Models by Simulation

Modifying model parameters.

Description

These functions can be used to change the size of a model's fixed effects, its random effect variance/covariance matrices, or its residual variance. This gives you more control over simulations from the model.

Usage

fixef(object) <- value

coef(object) <- value

VarCorr(object) <- value

sigma(object) <- value

scale(object) <- value

Arguments

object	a fitted model object.
value	new parameter values.

Details

New values for VarCorr are interpreted as variances and covariances, not standard deviations and correlations. New values for sigma and scale are interpreted on the standard deviation scale. This means that both VarCorr(object)<-VarCorr(object) and sigma(object)<-sigma(object) leave object unchanged, as you would expect.

sigma<- will only change the residual standard deviation, whereas scale<- will affect both sigma and VarCorr.

These functions can be used to change the value of individual parameters, such as a single fixed effect coefficient, using standard R subsetting commands.

See Also

getData if you want to modify the model's data.

Examples

fm <- lmer(y ~ x + (1|g), data=simdata)
fixef(fm)
fixef(fm)["x"] <- -0.1
fixef(fm)

pitakakariki/simr documentation built on April 22, 2023, 12:07 a.m.