get_prediction-method: Compute predicted value of formula for linear (mixed) model

In variancePartition: Quantify and interpret divers of variation in multilevel gene expression experiments

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))

variancePartition documentation built on Nov. 8, 2020, 5:18 p.m.