Optimal allocations for two treatment comparisons within the proportional odds cumulative logits model.

ABSTRACT: This paper studies optimal treatment allocations for two treatment comparisons when the outcome is ordinal and analyzed by a proportional odds cumulative logits model. The variance of the treatment effect estimator is used as optimality criterion. The optimal design is sought so that this variance is minimal for a given total sample size or a given budget, meaning that the power for the test on treatment effect is maximal, or it is sought so that a required power level is achieved at a minimal total sample size or budget. Results are presented for three, five and seven ordered response categories, three treatment effect sizes and a skewed, bell-shaped or polarized distribution of the response probabilities. The optimal proportion subjects in the intervention condition decreases with the nu

SUBMITTER: Moerbeek M 

PROVIDER: S-EPMC8059828 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature