Sample size estimation using a latent variable model for mixed outcome co-primary, multiple primary and composite endpoints.

ABSTRACT: Mixed outcome endpoints that combine multiple continuous and discrete components are often employed as primary outcome measures in clinical trials. These may be in the form of co-primary endpoints, which conclude effectiveness overall if an effect occurs in all of the components, or multiple primary endpoints, which require an effect in at least one of the components. Alternatively, they may be combined to form composite endpoints, which reduce the outcomes to a one-dimensional endpoint. There are many advantages to joint modeling the individual outcomes, however in order to do this in practice we require techniques for sample size estimation. In this article we show how the latent variable model can be used to estimate the joint endpoints and propose hypotheses, power calculations and sam

SUBMITTER: McMenamin ME 

PROVIDER: S-EPMC7612654 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature