Extracting Random Coefficients

Intro

This creates a table of random coefficients, i.e. fixed effects plus random effects. Uncertainty estimates are included where possible, but likely only accurate for Bayesian approaches.

Examples

library(lme4)
library(glmmTMB)
library(nlme)
library(brms)
library(mgcv)


lmer_model <-
  lmer(Reaction ~ Days + (1 + Days | Subject), data = sleepstudy)

lme_model  <-
  lme(Reaction ~ Days, random = ~ 1 + Days | Subject, data = sleepstudy)

tmb_model  <-
  glmmTMB(Reaction ~ Days + (1 + Days | Subject), data = sleepstudy)

# brms_model <-
#   brm(Reaction ~ Days + (1 + Days | Subject), 
#       data = sleepstudy,
#       cores = 4,
#       refresh = -1,
#       verbose = FALSE
#   )

# this is akin to (1 | Subject) + (0 + Days | Subject) in lme4
mgcv_model <-
  gam(
    Reaction ~  Days +
      s(Subject, bs = 're') +
      s(Days, Subject, bs = 're'),
    data   = lme4::sleepstudy,
    method = 'REML'
  )

library(mixedup)

head(extract_random_coefs(lmer_model))
 [38;5;246m# A tibble: 6 × 7 [39m
  group_var effect    group value    se lower_2.5 upper_97.5
   [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<fct> [39m [23m  [3m [38;5;246m<dbl> [39m [23m  [3m [38;5;246m<dbl> [39m [23m      [3m [38;5;246m<dbl> [39m [23m       [3m [38;5;246m<dbl> [39m [23m
 [38;5;250m1 [39m Subject   Intercept 308    254.  13.9      226.       281.
 [38;5;250m2 [39m Subject   Intercept 309    211.  13.9      184.       238.
 [38;5;250m3 [39m Subject   Intercept 310    212.  13.9      185.       240.
 [38;5;250m4 [39m Subject   Intercept 330    275.  13.9      248.       302.
 [38;5;250m5 [39m Subject   Intercept 331    274.  13.9      246.       301.
 [38;5;250m6 [39m Subject   Intercept 332    260.  13.9      233.       288.


head(extract_random_coefs(lme_model)) # different order
 [38;5;246m# A tibble: 6 × 6 [39m
  group_var effect group value lower_2.5 upper_97.5
   [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m   [3m [38;5;246m<chr> [39m [23m  [3m [38;5;246m<dbl> [39m [23m      [3m [38;5;246m<dbl> [39m [23m       [3m [38;5;246m<dbl> [39m [23m
 [38;5;250m1 [39m Subject   Days   308   19.7       7.42       13.5
 [38;5;250m2 [39m Subject   Days   309    1.85      7.42       13.5
 [38;5;250m3 [39m Subject   Days   310    5.02      7.42       13.5
 [38;5;250m4 [39m Subject   Days   330    5.65      7.42       13.5
 [38;5;250m5 [39m Subject   Days   331    7.40      7.42       13.5
 [38;5;250m6 [39m Subject   Days   332   10.2       7.42       13.5


head(extract_random_coefs(tmb_model))
 [38;5;246m# A tibble: 6 × 7 [39m
  group_var effect    group value    se lower_2.5 upper_97.5
   [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<fct> [39m [23m  [3m [38;5;246m<dbl> [39m [23m  [3m [38;5;246m<dbl> [39m [23m      [3m [38;5;246m<dbl> [39m [23m       [3m [38;5;246m<dbl> [39m [23m
 [38;5;250m1 [39m Subject   Intercept 308    254.  15.2      224.       284.
 [38;5;250m2 [39m Subject   Intercept 309    211.  15.3      181.       241.
 [38;5;250m3 [39m Subject   Intercept 310    213.  15.3      183.       243.
 [38;5;250m4 [39m Subject   Intercept 330    274.  15.4      244.       305.
 [38;5;250m5 [39m Subject   Intercept 331    273.  15.1      243.       303.
 [38;5;250m6 [39m Subject   Intercept 332    260.  14.5      232.       289.


head(extract_random_coefs(brms_model))
 [38;5;246m# A tibble: 6 × 7 [39m
  group_var effect    group value    se lower_2.5 upper_97.5
   [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m  [3m [38;5;246m<dbl> [39m [23m  [3m [38;5;246m<dbl> [39m [23m      [3m [38;5;246m<dbl> [39m [23m       [3m [38;5;246m<dbl> [39m [23m
 [38;5;250m1 [39m Subject   Intercept 308    253.  13.5      228.       279.
 [38;5;250m2 [39m Subject   Intercept 309    211.  13.2      185.       236.
 [38;5;250m3 [39m Subject   Intercept 310    212.  12.7      189.       235.
 [38;5;250m4 [39m Subject   Intercept 330    274.  12.9      247.       298.
 [38;5;250m5 [39m Subject   Intercept 331    274.  13.3      251.       296.
 [38;5;250m6 [39m Subject   Intercept 332    261.  13.4      235.       282.


head(extract_random_coefs(mgcv_model))
 [38;5;246m# A tibble: 6 × 7 [39m
  group_var effect    group value    se lower_2.5 upper_97.5
   [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m  [3m [38;5;246m<dbl> [39m [23m  [3m [38;5;246m<dbl> [39m [23m      [3m [38;5;246m<dbl> [39m [23m       [3m [38;5;246m<dbl> [39m [23m
 [38;5;250m1 [39m Subject   Intercept 308    253.  15.0      224.       282.
 [38;5;250m2 [39m Subject   Intercept 309    211.  15.0      182.       240.
 [38;5;250m3 [39m Subject   Intercept 310    212.  15.0      183.       242.
 [38;5;250m4 [39m Subject   Intercept 330    276.  15.0      247.       305.
 [38;5;250m5 [39m Subject   Intercept 331    274.  15.0      245.       304.
 [38;5;250m6 [39m Subject   Intercept 332    261.  15.0      231.       290.

Options

extract_random_coefs(
  lmer_model,
  ci_level = .9,
  digits   = 2
)
 [38;5;246m# A tibble: 36 × 7 [39m
   group_var effect    group value    se lower_5 upper_95
    [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<chr> [39m [23m      [3m [38;5;246m<fct> [39m [23m  [3m [38;5;246m<dbl> [39m [23m  [3m [38;5;246m<dbl> [39m [23m    [3m [38;5;246m<dbl> [39m [23m     [3m [38;5;246m<dbl> [39m [23m
 [38;5;250m 1 [39m Subject   Intercept 308    254.  13.9    231.     276.
 [38;5;250m 2 [39m Subject   Intercept 309    211.  13.9    188.     234.
 [38;5;250m 3 [39m Subject   Intercept 310    212.  13.9    190.     235.
 [38;5;250m 4 [39m Subject   Intercept 330    275.  13.9    252.     298.
 [38;5;250m 5 [39m Subject   Intercept 331    274.  13.9    251.     296.
 [38;5;250m 6 [39m Subject   Intercept 332    260.  13.9    238.     283.
 [38;5;250m 7 [39m Subject   Intercept 333    268.  13.9    245.     291.
 [38;5;250m 8 [39m Subject   Intercept 334    244.  13.9    221.     267.
 [38;5;250m 9 [39m Subject   Intercept 335    251.  13.9    228.     274.
 [38;5;250m10 [39m Subject   Intercept 337    286.  13.9    263.     309.
 [38;5;246m# … with 26 more rows [39m

Michael Clark

2022-10-10

Intro

Examples

Options