- Information about the model intercept and coefficients
- Information about the regression (number of iterations and number of rows processed) and several goodness-of-fit measures
Columns
| Column | Description |
|---|---|
| predictor |
Name of predictor or other reported result. For categorical predictors, the function selects one category as the reference category, and outputs one row for each other category for the column, in the format predictor.level. For example, if column color has categories 'red', 'blue', and 'green', and green is the reference category, the function outputs these rows: color.red color.blue |
| estimate | For predictors, estimated value of coefficient. For other reported results, calculated value. |
| std_error | For predictors, standard deviation of the mean (standard error). For other reported results, not applicable (value 0). |
| z_score | For predictors, calculated z-score. For other reported results, calculated value. |
| p_value | For predictors, calculated p-value. For other reported results, not applicable (value 0). |
| significance | For predictors, indicator of predictor significance. For key to significance codes, see CoxPH Output. For other reported results, description of result. |
Rows
The onscreen output includes a row for each estimated parameter of the model and additional information about the model and the regression.
For Step ('true'), the rows of the following tables appear for the model at each step and describe the model at that step. For each step, the description includes only the predictors included in the model.
| Parameter | Description |
|---|---|
| (Intercept) | Value of link function (Y) when all predictors are 0. |
| predictor | [Appears only for numerical predictor.] Predictor name. |
| predictor.level | [Appears only for categorical predictor.] Predictor name and level. Table has a row for each level of the predictor except one, which serves as the reference level. |
| Value | Description |
|---|---|
| ITERATIONS# | Number of Fisher Scoring iterations performed on function. With Step ('true'), function reports this number for each step.
|
| ROWS# | Number of rows of data received as input. |
| Residual deviance | Deviance, with degrees of freedom reported in significance column. Residual deviance is not displayed when Family is GAMMA, NEGATIVE_BINOMIAL, or INVERSE_GAUSSIAN.
|
| Pearson goodness of fit | Sum of squared Pearson residual. |
| AIC | Akaike information criterion, a measure of relative quality of model for given data set. |
| BIC | Bayesian information criterion, partly based on likelihood function and closely related to AIC. BIC is a criterion for model selection among a finite set of models; the model with the lowest BIC is preferred. |
| Wald Test | Tests goodness of fit. |
| Dispersion parameter | For GAUSSIAN, the value of this parameter is estimated from the data. For all other families, this parameter value is 1. |
The coefficients are also stored in the table output_table for later use.