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Estimating odds and log odds with guaranteed accuracy
Luis Mendo
https://arxiv.org/abs/2404.17705 https://arxiv.org/pdf/2404.17705

Estimating odds and log odds with guaranteed accuracy
Two sequential estimators are proposed for the odds p/(1-p) and log odds log(p/(1-p)) respectively, using independent Bernoulli random variables with parameter p as inputs. The estimators are unbiased, and guarantee that the variance of the estimation error divided by the true value of the odds, or the variance of the estimation error of the log odds, are less than a target value for any p in (0,1). The estimators are close to optimal in the sense of Wolfowitz's bound.

This https://arxiv.org/abs/2310.10271 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

A geometric power analysis for general log-linear models
Log-linear models are widely used to express the association in multivariate frequency data on contingency tables. The paper focuses on the power analysis for testing the goodness-of-fit hypothesis for this model type. Conventionally, for the power-related sample size calculations a deviation from the null hypothesis (effect size) is specified by means of the chi-square goodness-of-fit index. It is argued that the odds ratio is a more natural measure of effect size, with the advantage of having…