Table 3 Description of the closed testing procedure for updating of multinomial logistic regression models
From: Validation and updating of risk models based on multinomial logistic regression
| Step | Procedure |
|---|---|
| 1. Original model vs refitting |
H0: both models have the same fit, log L
original = log L
refitted. Test: likelihood ratio test with (q + 1) × (k − 1)df. Result: if H0 not rejected, choose the original model, else go to step 2. |
| 2. Intercept recalibration vs refitting |
H0: both models have the same fit, log L
int recal = log L
refitted. Test: likelihood ratio test with q × (k − 1)df. Result: if H0 not rejected, choose intercept recalibration, else go to step 3. |
| 3. Logistic recalibration vs refitting |
H0: both models have the same fit, log L
logrecal = log L
refitted. Test: likelihood ratio test with (q − k + 1) × (k − 1)df. Result: if H0 not rejected, choose logistic recalibration, else choose refitting. |