Estimation of required sample size for external validation of risk models for binary outcomes.

ABSTRACT: Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is choosing an adequate sample size. In this paper, we investigate the sample size requirements for validation studies with binary outcomes to estimate measures of predictive performance (C-statistic for discrimination and calibration slope and calibration in the large). We aim for sufficient precision in the estimated measures. In addition, we investigate the sample size to achieve sufficient power to detect a difference from a target value. Under normality assumptions on the distribution of the linear predictor, we obtain simple estimators for sample size calculation

SUBMITTER: Pavlou M 

PROVIDER: S-EPMC8529102 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature