2022-03-18
Anytime-valid confidence intervals for contingency tables and beyond
Publication
Publication
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.
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Organisation | Machine Learning |
Turner, R., & Grünwald, P. (2022). Anytime-valid confidence intervals for contingency tables and beyond. |