get_prediction {variancePartition} | R Documentation

## Compute predicted value of formula for linear (mixed) model

### Description

Compute predicted value of formula for linear (mixed) model for with `lm` or `lmer`

### Usage

    get_prediction(fit, formula)

    ## S4 method for signature 'lmerMod'
    get_prediction(fit, formula)

    ## S4 method for signature 'lm'
    get_prediction(fit, formula)

### Arguments

`fit` | model fit with `lm` or `lmer`
`formula` | formula of fixed and random effects to predict

### Details

Similar motivation as `lme4:::predict.merMod()`, but that function cannot use just a subset of the fixed effects: it either uses none or all. Note that the intercept is included in the formula by default. To exclude it from the prediction use `~ 0 + ...` syntax

### Value

Predicted values from formula using parameter estimates from fit linear (mixed) model

### Examples

    library(lme4)

    # Linear model
    fit <- lm(Reaction ~ Days, sleepstudy)

    # prediction of intercept
    get_prediction( fit, ~ 1)

    # prediction of Days without intercept
    get_prediction( fit, ~ 0 + Days)

    # Linear mixed model

    # fit model
    fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)

    # predict Days, but exclude intercept
    get_prediction( fm1, ~ 0 + Days)

    # predict Days and (Days | Subject) random effect, but exclude intercept
    get_prediction( fm1, ~ 0 + Days +  (Days | Subject))

[Package variancePartition version 1.22.0 Index]