Linear mixed effects parameters
Fixed Effects formula faith_pd ~ Q('day-relative-to-fmt') * autoFmtGroup
Metric faith_pd
Group column [autoFmtGroup]
State column day-relative-to-fmt
Individual ID column PatientID
Random effects None

Model summary

model summary
Model: MixedLM
No. Observations: 356
No. Groups: 24
Min. group size: 2
Max. group size: 34
Mean group size: 14.8
Dependent Variable: faith_pd
Method: REML
Scale: 7.0204
Log-Likelihood: -869.3730
Converged: Yes

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Model results

Coef. Std.Err. z P>|z| [0.025 0.975]
Intercept 6.456 0.436 14.792 0.000 5.600 7.311
autoFmtGroup[T.treatment] -0.082 0.576 -0.142 0.887 -1.210 1.047
Q('day-relative-to-fmt') -0.061 0.011 -5.612 0.000 -0.082 -0.040
Q('day-relative-to-fmt'):autoFmtGroup[T.treatment] 0.035 0.015 2.369 0.018 0.006 0.064
Group Var 0.893 0.163

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Regression scatterplots

Projected Residuals

Fit values for metric vs. observation error (residuals). Residuals should be roughly zero-centered and normal. Uncentered, systematically high or low, and autocorrelated values could indicate a poor model.