monet

monet provides an interface for Type III tests of model terms for any user-provided estimation function: test_terms.
This is achieved by estimating a full model including all model terms, as well as restricted models in which the parameters corresponding to one model term are withhold (i.e., set to zero). The test between the full model and the restricted model can be performed via any user-provided model comparison function, the default uses the generic anova function. In some sense, monet provides a generalization to afex::mixed.

The name monet is basically a portmanteau based on the fact that this package provides MOdel comparisons for NEsTed models.

Installation

You can install monet from github with:

# install.packages("devtools")
devtools::install_github("singmann/monet")

Example

The main function is test_terms:

set_sum_contrasts() ## quite important, currently coding is not checked

data("Machines", package = "MEMSS")

# ignoring repeated-measures
m1 <- test_terms(score ~ Machine, data=Machines,
                 est_fun = lm)
m1
# lm Anova Table (Type III tests)
# 
# Model: score ~ Machine
# Data: Machines
#    Effect Df 1 Df 0         F Pr(>F)
# 1 Machine   51    2 26.30 *** <.0001
# ---
# Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘+’ 0.1 ‘ ’ 1
nice(m1)
anova(m1)

# simple model with random-slopes for repeated-measures factor
m3 <- test_terms(score ~ Machine, data=Machines,
                 extra_formula = ~ (Machine|Worker),
                 est_fun = lme4::lmer, arg_est = list(REML = FALSE),
                 arg_test = list(model.names=c("f", "r")))
m3
# lme4::lmer Anova Table (Type III tests)
# 
# Model: score ~ Machine + (Machine | Worker)
# Data: Machines
#    Effect Df 1 Df 0     Chisq Pr(>Chisq)
# 1 Machine   10    2 17.14 ***      .0002
# ---
# Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘+’ 0.1 ‘ ’ 1
anova(m3)

## replicates:
afex::mixed(score ~ Machine + (Machine|Worker), data=Machines, method = "LRT")
# Mixed Model Anova Table (Type 3 tests, LRT-method)
# 
# Model: score ~ Machine + (Machine | Worker)
# Data: Machines
# Df full model: 10
#    Effect df     Chisq p.value
# 1 Machine  2 17.14 ***   .0002
# ---
# Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘+’ 0.1 ‘ ’ 1