This function takes two logistic regression models \(M_A, M_B\), test data, significance level \(\alpha\) and allowed flips ratio \(r\). It checks whether the models produce equivalent log-odds for the given test set and returns various figures.
individual_predictive_equiv(model_a, model_b, test_data, r = 0.1, alpha = 0.05)logistic regression model \(M_A\)
logistic regression model \(M_B\)
testing dataset
ratio of allowed 'flips' (defaults to 0.1)
significance level \(\alpha\) (defaults to 0.05)
equivalenceAre models \(M_A,M_B\) producing equivalent log-odds for the given test data? (boolean)
test_statisticThe test statistic
critical_valuea level-\(\alpha\) critical value the test
xi_barMean \(\xi\) value for the test
delta_thetaCalculated equivalence parameter
p_valueP-value