Exact-corrected confidence interval for risk difference in noninferiority binomial trials

04/10/2021 ∙ by Nour Hawila, et al. ∙ 0

A novel confidence interval estimator is proposed for the risk difference in noninferiority binomial trials. The confidence interval is consistent with an exact unconditional test that preserves the type-1 error, and has improved power, particularly for smaller sample sizes, compared to the confidence interval by Chan Zhang (1999). The improved performance of the proposed confidence interval is theoretically justified and demonstrated with simulations and examples. An R package is also distributed that implements the proposed methods along with other confidence interval estimators.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 11

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.