2 papers
stat.ME2026
Addressing errors in multiple variables using generalized raking and cumulative probability models
Eric S. Kawaguchi, Chun Li, Frank E. Harrell +3
Routinely collected data, such as electronic health record (EHR) data, are frequently used for biomedical research, but these data are prone to errors, which can bias study finding…
stat.ME2025
A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- part 1: binary outcomes
Richard D Riley, Gary S Collins, Rebecca Whittle +11
When developing a clinical prediction model, the sample size of the development dataset is a key consideration. Small sample sizes lead to greater concerns of overfitting, instabil…