report.lmer.md
In report: Automated Reporting of Results and Statistical Models

report-lmer

Code
  report(m1)
Output
  We fitted a linear mixed model (estimated using REML and nloptwrap optimizer)
  to predict Reaction with Days (formula: Reaction ~ Days). The model included
  Days as random effects (formula: ~1 + Days | Subject). The model's total
  explanatory power is substantial (conditional R2 = 0.80) and the part related
  to the fixed effects alone (marginal R2) is of 0.28. The model's intercept,
  corresponding to Days = 0, is at 251.41 (95% CI [237.94, 264.87], t(174) =
  36.84, p < .001). Within this model:

    - The effect of Days is statistically significant and positive (beta = 10.47,
  95% CI [7.42, 13.52], t(174) = 6.77, p < .001; Std. beta = 0.54, 95% CI [0.38,
  0.69])

  Standardized parameters were obtained by fitting the model on a standardized
  version of the dataset. 95% Confidence Intervals (CIs) and p-values were
  computed using a Wald t-distribution approximation.

Code
  report(m2)
Message
  boundary (singular) fit: see help('isSingular')
Output
  Random effect variances not available. Returned R2 does not account for random effects.
Message
  boundary (singular) fit: see help('isSingular')
Output
  Random effect variances not available. Returned R2 does not account for random effects.
  We fitted a linear mixed model (estimated using REML and nloptwrap optimizer)
  to predict Reaction with Days (formula: Reaction ~ Days). The model included
  mysubgrp as random effects (formula: list(~1 | mysubgrp:mygrp, ~1 | mygrp, ~1 |
  Subject)). The model's explanatory power related to the fixed effects alone
  (marginal R2) is 0.49. The model's intercept, corresponding to Days = 0, is at
  252.09 (95% CI [232.50, 271.69], t(174) = 25.39, p < .001). Within this model:

    - The effect of Days is statistically significant and positive (beta = 10.35,
  95% CI [8.78, 11.93], t(174) = 12.95, p < .001; Std. beta = 0.53, 95% CI [0.45,
  0.61])

  Standardized parameters were obtained by fitting the model on a standardized
  version of the dataset. 95% Confidence Intervals (CIs) and p-values were
  computed using a Wald t-distribution approximation.