Anytime-valid confidence intervals for contingency tables and beyond
E variables are tools for designing tests that keep their type-I error guarantees under flexible sampling scenarios such as optional stopping and continuation. We extend the recently developed E variables for two-sample tests to general null hypotheses and the corresponding anytime-valid confidence sequences. Using the 2x2 contingency table (Bernoulli) setting as a running example, we provide simple implementations of these confidence sequences for linear and odds-ratio based effect size.
Turner, R.J, & Grünwald, P.D. (2022). Anytime-valid confidence intervals for contingency tables and beyond.