The output table shows the model statistics.
predictor | estimate | std_error | z_score | p_value | significance |
---|---|---|---|---|---|
(Intercept) | 1.07751 | 2.92076 | 0.368914 | 0.712192 | |
masters.no | 2.21655 | 1.01999 | 2.17311 | 0.0297719 | * |
gpa | -0.113935 | 0.802573 | -0.141962 | 0.88711 | |
stats.Novice | 0.0406848 | 1.11567 | 0.0364667 | 0.97091 | |
stats.Beginner | 0.526618 | 1.2229 | 0.430631 | 0.666736 | |
programming.Beginner | -1.76976 | 1.069 | -1.65553 | 0.0978177 | . |
programming.Novice | -0.98035 | 1.14004 | -0.859923 | 0.389831 | |
ITERATIONS # | 4 | 0 | 0 | 0 | Number of Fisher Scoring iterations |
ROWS # | 40 | 0 | 0 | 0 | Number of rows |
Residual deviance | 38.9038 | 0 | 0 | 0 | on 33 degrees of freedom |
Pearson goodness of fit | 37.7905 | 0 | 0 | 0 | on 33 degrees of freedom |
AIC | 52.9038 | 0 | 0 | 0 | Akaike information criterion |
BIC | 64.726 | 0 | 0 | 0 | Bayesian information criterion |
Wald Test | 9.89642 | 0 | 0 | 0.19452 | |
Dispersion parameter | 1 | 0 | 0 | 0 | Taken to be 1 for BINOMIAL and POISSON. |
For categorical variables, the model selects a reference category. In this example, the Advanced category was used as a reference for the stats variable.
The query below returns the output shown in the following table:
SELECT * FROM glm_admissions_model ORDER BY attribute;
The example uses stepwise selection only to show which predictors are included in the regression. The predicted output models are not used in any prediction function. The following table is only a collection of the coefficients estimated in each step.
attribute | predictor | category | estimate |
---|---|---|---|
-1 | Loglik | -19.4519 | |
0 | (Intercept) | 1.0775 | |
1 | masters | yes | |
2 | masters | no | 2.21655 |
3 | gpa | -0.113935 | |
4 | stats | Advanced | |
5 | stats | Novice | 0.0406848 |
6 | stats | Beginner | 0.526618 |
7 | programming | Advanced | |
8 | programming | Beginner | -1.76976 |
9 | programming | Novice | -0.98035 |
std_err | z_score | p_value | significance |
---|---|---|---|
40 | 6 | 0 | |
2.92076 | 0.368914 | 0.712192 | |
1.01999 | 2.17311 | 0.0297719 | * |
0.802573 | -0.141962 | 0.88711 | |
1.11567 | 0.0364667 | 0.97091 | |
1.2229 | 0.430631 | 0.666736 | |
1.069 | -1.65553 | 0.0978177 | . |
1.14004 | -0.859923 | 0.389831 |