Glm run #190 · statistical_test
4.918e-15
p value
negative_binomial
family
593.5
aic
16.88
deviance
completed
status
2026-09-21 02:16
created
Figures
Coefficient estimates (95% CI)
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Observed vs fitted
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Residuals vs fitted
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Coefficients 2 rows
| term | coef | se | z | p | ci_lower | ci_upper |
|---|---|---|---|---|---|---|
| const | 0.4955632056834583 | 0.21611704862814335 | 2.2930315254125895 | 0.021846190031803388 | 0.07198157392720583 | 0.9191448374397108 |
| predictor | 0.29685465316907605 | 0.03791740377876027 | 7.828981512055989 | 4.918379542703251e-15 | 0.222537907375443 | 0.3711713989627091 |
Method & Provenance
- Method
- Count GLM (Poisson / Negative Binomial)
- Method key
glm(result type:statistical_test, result #190)- Engine
- Python · statsmodels v0.14.6
- Dataset(s)
- #708 gallery — example_glm_counts.csv
- Status
- completed
- Permanent link
- https://cat-g-omxpert.wishartlab.com/results/by-token/d9e9c78bde024ef2898ba52fc898c183 Bookmark or share this URL — it does not depend on your session.
- Created
- 2026-09-21 02:16:53.486314
Parameters used
| Parameter | Value |
|---|---|
test_type
| glm |
value_col
| count |
predictor_cols
| predictor |
Execution trace
Reconstructed from the parameters stored with this result — represents the Python/R calls the analysis service made.
import statsmodels.api as smmodel = sm.GLM(y_counts, X_predictors, family=sm.families.Poisson())fit = model.fit()