A practical solution to estimate the sample size required for clinical prediction models generated from observational research on data.

Carlos Baeza-DelgadoLeonor Cerdá AlberichJosé Miguel Carot-SierraDiana Veiga-CanutoBlanca Martínez de Las HerasBen RazaLuis Martí-Bonmatí

Published in: European radiology experimental (2022)

Given the variability of the different sample sizes obtained, we recommend using methods based on epidemiological data and the nature of the results, as the results are tailored to the specific clinical problem. In addition, sample size can be reduced by lowering the number of parameter predictors, by including direct measures of the outcome of interest.

Keyphrases

electronic health record
big data
cross sectional
data analysis
solid state