Result Detail – Lmm

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Notebook
Result Information
Result ID
188
Type
Lmm
Status
completed
Dataset ID
707
Created
2026-09-21 02:16:46.041991
Statistical Test Result
Test
lmm — lmm
Statistic
—
p-value
6.37e-08
Interpretation
significant Linear mixed model: value ~ C(treatment) — smallest fixed-effect p = 6.37e-08
Value Column
value
Group Column
subject
Observations
120 — 40 groups
Model coefficients value ~ C(treatment)
TermCoefSE95% CIzp
Intercept 9.6288 0.4638 [8.720, 10.538] 20.760 9.865e-96
C(treatment)[T.treated] 3.5473 0.6559 [2.262, 4.833] 5.408 6.37e-08
Group Var 4.0937 1.2335 [1.676, 6.511] 3.319 0.000904

Model converged. n = 120 observations across 40 groups (random intercepts).

Figures
Coefficient estimates (95% CI) Download PNG
Coefficient estimates (95% CI)
Observed vs fitted Download PNG
Observed vs fitted
Residuals vs fitted Download PNG
Residuals vs fitted
Pathway Analysis (same dataset) Help
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Method & Provenance

Method
Linear mixed-effects model (random intercept)
Method key
lmm (result type: statistical_test, result #188)
Engine
Python · statsmodels v0.14.6
Dataset(s)
#707 gallery — example_lmm.csv
Status
completed
Permanent link
https://cat-g-omxpert.wishartlab.com/results/by-token/a59b0a0c337b4536a6b291f072aadf18 Bookmark or share this URL — it does not depend on your session.
Created
2026-09-21 02:16:46.041991

Parameters used

ParameterValue
test_type lmm
value_col value
group_col subject
fixed_col treatment

Execution trace

Reconstructed from the parameters stored with this result — represents the Python/R calls the analysis service made. 

import statsmodels.formula.api as smf
model = smf.mixedlm('value ~ fixed', data=df, groups=df['group_col'])
fit = model.fit()