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. 2017 Feb 8;1:2. doi: 10.1186/s41512-016-0002-x

Table 3.

Description of the closed testing procedure for updating of multinomial logistic regression models

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.

Each test is performed at the prespecified overall alpha level

H0 null hypothesis, L likelihood, df degrees of freedom