Modifying model parameters.
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.
fixef(object) <- value coef(object) <- value VarCorr(object) <- value sigma(object) <- value scale(object) <- value
object: a fitted model object.value: new parameter values.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.
fm <- lmer(y ~ x + (1|g), data=simdata) fixef(fm) fixef(fm)["x"] <- -0.1 fixef(fm)
getData if you want to modify the model's data.