APAze: APA6-ready output for (g)lm , (g)lmer objects and Bayes...

In neuropsychology: Toolbox for Psychologists, Neuropsychologists and Neuroscientists

Description

APA6-ready output for mixed effects and non-mixed effects linear models.

Usage

APAze(fit,
      method="Wald",
      nsim=1000,
      add.stars=TRUE,
      ddf=NULL)

Arguments

fit	A (g)lm or lme4::(g)lmer fit.
method	"boot" for bootstrapped CI, "Wald" for estimated. Only in the case of a mixed-effect model. See confint.merMod.
nsim	how many times should it bootstrap the confindence intervals (only if method = "boot").
add.stars	Add significance stars.
ddf	Denominator degrees of freedom approximation (only if fit is an instance of lmerTest::merModLmerTest, ignored otherwise). If 'NULL', then the normal approximation (treat t-values as z-values) is used for lmer objects fit with lme4 and the default Satterthwaite is used for models fit with lmerTest.

Author(s)

Dominique Makowski, Phillip Alday

Examples

require(neuropsychology)

df <- personality

fit <- lme4::lmer(Age ~ BMI + (1|Salary), data=df)
APAze(fit, method="Wald")

Example output

Loading required package: tidyverse
-- Attaching packages --------------------------------------- tidyverse 1.2.1 --
v ggplot2 3.1.1       v purrr   0.3.2  
v tibble  2.1.1       v dplyr   0.8.0.1
v tidyr   0.8.3       v stringr 1.4.0  
v readr   1.3.1       v forcats 0.4.0  
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
************
Welcome to neuropsychology v0.5.0 (c) Dominique Makowski.
See documentation on https://www.rdocumentation.org/packages/neuropsychology
Do not hesitate to create an issue on https://github.com/neuropsychology/neuropsychology.R/issues with questions, comments, or movie recommendations.
************
[1] "The overall model predicting Age successfully converged and explained 43% of the variance of the endogen (the conditional R2). The variance explained by the fixed effects was of 04% (the marginal R2) and the one explained by the random effects of 39%."
[2] "(Intercept): (beta = 22.25, 95% CI [15.24, 29.27], p < .001***)"                                                                                                                                                                                            
[3] "BMI: (beta = 0.57, 95% CI [0.42, 0.72], p < .001***)"                                                                                                                                                                                                       

neuropsychology documentation built on May 2, 2019, 2:13 p.m.