tests/testthat/_snaps/avg_predictions.md

In ggeffects: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

ggpredict, condition

Code
  print(out1)
Output
  # Average predicted values of Negative impact with 7 items

  c172code: low level of education

  c12hour | Predicted |       95% CI
  ----------------------------------
       20 |     11.49 | 10.78, 12.20
       30 |     11.55 | 10.85, 12.26
       40 |     11.62 | 10.92, 12.31

  c172code: intermediate level of education

  c12hour | Predicted |       95% CI
  ----------------------------------
       20 |     11.65 | 11.09, 12.21
       30 |     11.71 | 11.17, 12.26
       40 |     11.78 | 11.23, 12.32

  c172code: high level of education

  c12hour | Predicted |       95% CI
  ----------------------------------
       20 |     12.22 | 11.48, 12.95
       30 |     12.28 | 11.55, 13.01
       40 |     12.34 | 11.61, 13.07

ggaverage, glm

Code
  print(out1)
Output
  # Average predicted probabilities of neg_c_7d

  c172code: low level of education

  c12hour | Predicted |     95% CI
  --------------------------------
       20 |      0.39 | 0.32, 0.48
       30 |      0.40 | 0.32, 0.48
       40 |      0.41 | 0.33, 0.49

  c172code: intermediate level of education

  c12hour | Predicted |     95% CI
  --------------------------------
       20 |      0.40 | 0.36, 0.46
       30 |      0.41 | 0.36, 0.46
       40 |      0.42 | 0.37, 0.47

  c172code: high level of education

  c12hour | Predicted |     95% CI
  --------------------------------
       20 |      0.47 | 0.38, 0.55
       30 |      0.48 | 0.39, 0.56
       40 |      0.48 | 0.40, 0.57

ggeffects documentation built on Sept. 12, 2024, 7:41 a.m.