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Exact Anytime-valid Confidence Intervals for Contingency Tables and Beyond
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E-variables are tools for retaining type-I error guarantee with optional stopping. We extend E-variables for sequential two-sample tests to general null hypotheses and anytime-valid confidence sequences. We provide implementations for estimating risk difference, relative risk and odds-ratios in contingency tables.
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Cited by 1 Pith paper
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Efficient Sequential Evaluation of Large Language Models
A confidence-sequence framework for sequentially estimating an LLM's average benchmark accuracy under adaptive question selection, with growth-oriented sampling rules that in practice often lose to uniform sampling.
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