Analyze coefficient uncertainty with simple inputs. Generate interval tables for logit, Poisson, and related models. Export clean results and validate assumptions with example data.
| Coefficient | Estimate | SE | DF | Model Note |
|---|---|---|---|---|
| Intercept | 0.8500 | 0.2200 | 120 | Baseline log outcome |
| Age | 0.0350 | 0.0110 | 120 | Continuous predictor |
| Treatment | -0.4100 | 0.1600 | 120 | Binary group effect |
| Exposure | 0.1200 | 0.0500 | 120 | Rate model input |
The calculator applies a Wald style interval for each coefficient.
Margin of Error = Critical Value × Standard Error
Lower Limit = Estimate − Margin of Error
Upper Limit = Estimate + Margin of Error
For normal based intervals, the critical value comes from the standard normal distribution. For t based intervals, the critical value uses the chosen degrees of freedom.
When exponentiation is enabled, the transformed interval becomes exp(beta), exp(lower), and exp(upper). This is useful for odds ratios and rate ratios in common generalized linear models.
A generalized linear model estimates how predictors shift a target outcome. The coefficient alone is not enough. You also need uncertainty. This calculator builds confidence intervals for each coefficient, so you can judge precision, direction, and practical stability. It works well for logistic, Poisson, and other common GLM settings.
A point estimate can look strong, yet still be unreliable. A confidence interval shows the likely range for the true parameter under repeated sampling logic. Narrow intervals suggest better precision. Wide intervals suggest caution. When an interval crosses zero, the coefficient may not be clearly separated from no effect on the link scale.
The tool uses the estimate, its standard error, and a critical value. The margin of error equals the critical value multiplied by the standard error. The lower and upper limits are built around the estimate. This is the standard Wald interval approach used in many reports, dashboards, and model review workflows.
Many GLMs use a log or logit link. In those cases, the raw coefficient may be hard to explain. Exponentiating the estimate and interval gives a ratio scale. In logistic regression, that ratio is often interpreted as an odds ratio. In Poisson style models, it can represent a multiplicative rate effect.
Focus on four checks. First, review the coefficient sign. Second, inspect interval width. Third, see whether zero lies inside the raw interval. Fourth, compare exponentiated limits when you need practical interpretation. These steps help you explain whether a predictor is uncertain, stable, weak, or meaningfully associated with the modeled response.
This page keeps the workflow simple. You can enter several coefficients, compare interval widths, export clean tables, and test reporting choices quickly. That makes it useful for model audits, teaching, consulting, and technical documentation. It is especially helpful when you need a fast coefficient interval check without rebuilding the original model output.
It calculates confidence intervals for GLM coefficients using the estimate, standard error, confidence level, and selected critical value method.
Z intervals are common for large samples. T intervals can be helpful when you want degrees of freedom to influence the critical value.
Exponentiation makes many GLM coefficients easier to interpret. It converts log scale effects into odds ratios or rate ratios for common link functions.
If the raw interval includes zero, the coefficient is not clearly separated from no effect on the link scale at that confidence level.
Yes. Add as many rows as needed. The calculator processes each valid coefficient and returns a combined result table.
No. This tool does not estimate coefficients from raw data. It only summarizes interval estimates from values you already have.
Large positive coefficients can produce very large exponentiated values. That usually reflects the scale of the link function and the coefficient magnitude.
Yes. The results section includes CSV export for tables and a PDF option through the browser print workflow.