performance_equiv: performance_equiv function

In LogRegEquiv: Logistic Regression Equivalence

performance_equiv function

Description

This function takes two logistic regression models M_A, M_B, test data, significance level α and acceptable score degradation δ_B. It checks whether the models perform equivalently on the test set and returns various figures.

Usage

performance_equiv(
  model_a,
  model_b,
  test_data,
  dv_index,
  delta_B = 1.1,
  alpha = 0.05
)

Arguments

model_a	logistic regression model M_A
model_b	logistic regression model M_B
test_data	testing dataset
dv_index	column number of the dependent variable
delta_B	acceptable score degradation (defaults to 1.1)
alpha	significance level α (defaults to 0.05)

Value

equivalence

Are models M_A,M_B producing equivalent Brier scores for the given test data? (boolean)

brier_score_ac

M_A Brier score on the testing data

brier_score_bc

M_B Brier score on the testing data

diff_sd_l

SD of the lower Brier difference BS^A-δ_B^2BS^B

diff_sd_u

SD of the upper Brier difference BS^A-δ_B^{-2}BS^B

test_stat_l

t_L equivalence boundary for the test

test_stat_u

t_U equivalence boundary for the test

crit_val

a level-α critical value for the test

delta_B

Calculated equivalence parameter

p_value_l

P-value for t_L

p_value_u

P-value for t_U

LogRegEquiv documentation built on March 18, 2022, 6:13 p.m.