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🎓 Tidy multilevel modeling tools for academics

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tidymlm

lifecycle

🎓 Tidy tools for academics

*** This package is in very early development. Feedback is encouraged!!! ***

Installation

Install the development version from Github with:

## install devtools if not already
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}
## install tidymlm from Github
devtools::install_github("mkearney/tidymlm")

Load the package (it, of course, plays nicely with tidyverse).

## load tidyverse
library(tidyverse)

## load tidymlm
library(tidymlm)

Multilevel modeling (MLM)

Estimate multilevel (mixed effects) models.

lme4::sleepstudy %>%
  tidy_mlm(Reaction ~ Days + (Days | Subject)) %>%
  summary()
#> Linear mixed model fit by REML ['lmerMod']
#> Formula: Reaction ~ Days + (Days | Subject)
#>    Data: .data
#> 
#> REML criterion at convergence: 1743.6
#> 
#> Scaled residuals: 
#>    Min     1Q Median     3Q    Max 
#> -3.954 -0.463  0.023  0.463  5.179 
#> 
#> Random effects:
#>  Groups   Name        Variance Std.Dev. Corr
#>  Subject  (Intercept) 612.1    24.74        
#>           Days         35.1     5.92    0.07
#>  Residual             654.9    25.59        
#> Number of obs: 180, groups:  Subject, 18
#> 
#> Fixed effects:
#>             Estimate Std. Error t value
#> (Intercept)   251.41       6.82   36.84
#> Days           10.47       1.55    6.77
#> 
#> Correlation of Fixed Effects:
#>      (Intr)
#> Days -0.138

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