complete_separation.md
In parameters: Processing of Model Parameters

print warning about complete separation

Code
  print(out)
Output
  Parameter   | Log-Odds |       SE |                95% CI |         z |      p
  ------------------------------------------------------------------------------
  (Intercept) |   -66.10 | 1.83e+05 | [-10644.72, 10512.52] | -3.60e-04 | > .999
  x1          |    15.29 | 27362.84 | [ -3122.69,         ] |  5.59e-04 | > .999
  x2          |     6.24 | 81543.72 | [-12797.28,         ] |  7.65e-05 | > .999
Message

  Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
    computed using a Wald z-distribution approximation.

  The model has a log- or logit-link. Consider using `exponentiate =
    TRUE` to interpret coefficients as ratios.

  Some coefficients are very large, which may indicate issues with
    complete separation.

Code
  print(out)
Output
  Parameter   | Log-Odds |       SE |            95% CI |         z |     p
  -------------------------------------------------------------------------
  (Intercept) |   -83.33 | 15505.03 | [       , 816.56] | -5.37e-03 | 0.996
  gear        |    21.01 |  3876.26 | [-248.93,       ] |  5.42e-03 | 0.996
Message

  Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
    computed using a Wald z-distribution approximation.

  The model has a log- or logit-link. Consider using `exponentiate =
    TRUE` to interpret coefficients as ratios.

  Some coefficients are very large, which may indicate issues with
    complete separation.

print warning about quasi complete separation

Code
  print(out)
Output
  Parameter   | Log-Odds |    SE |         95% CI |     z |     p
  ---------------------------------------------------------------
  (Intercept) |   -70.25 | 88.29 | [    , -16.06] | -0.80 | 0.426
  qsec        |     4.12 |  5.22 | [0.97,       ] |  0.79 | 0.430
Message

  Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
    computed using a Wald z-distribution approximation.

  The model has a log- or logit-link. Consider using `exponentiate =
    TRUE` to interpret coefficients as ratios.

  Some coefficients seem to be rather large, which may indicate issues
    with (quasi) complete separation. Consider using bias-corrected or
    penalized regression models.