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: | 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 |
Download summary as tsv
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 |
Download results as tsv
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.