结果(博弈论)
统计的
样本量测定
统计
二进制数
样品(材料)
计算机科学
差异(会计)
事件(粒子物理)
数学
计量经济学
物理
数理经济学
热力学
会计
业务
量子力学
算术
作者
Richard D Riley,Ben Van Calster,Gary S. Collins
摘要
In 2019 we published a pair of articles in Statistics in Medicine that describe how to calculate the minimum sample size for developing a multivariable prediction model with a continuous outcome, or with a binary or time‐to‐event outcome. As for any sample size calculation, the approach requires the user to specify anticipated values for key parameters. In particular, for a prediction model with a binary outcome, the outcome proportion and a conservative estimate for the overall fit of the developed model as measured by the Cox‐Snell R 2 (proportion of variance explained) must be specified. This proposal raises the question of how to identify a plausible value for R 2 in advance of model development. Our articles suggest researchers should identify R 2 from closely related models already published in their field. In this letter, we present details on how to derive R 2 using the reported C statistic (AUROC) for such existing prediction models with a binary outcome. The C statistic is commonly reported, and so our approach allows researchers to obtain R 2 for subsequent sample size calculations for new models. Stata and R code is provided, and a small simulation study.
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