McMurry Timothy L, Poplin Gerald S
a University of Virginia Department of Public Health Sciences , Charlottesville , Virginia.
Traffic Inj Prev. 2015;16(6):618-26. doi: 10.1080/15389588.2014.991820. Epub 2014 Dec 31.
We address 4 frequently misunderstood and important statistical ideas in the construction of injury risk functions. These include the similarities of survival analysis and logistic regression, the correct scale on which to construct pointwise confidence intervals for injury risk, the ability to discern which form of injury risk function is optimal, and the handling of repeated tests on the same subject.
The statistical models are explored through simulation and examination of the underlying mathematics.
We provide recommendations for the statistically valid construction and correct interpretation of single-predictor injury risk functions.
This article aims to provide useful and understandable statistical guidance to improve the practice in constructing injury risk functions.
我们探讨在构建损伤风险函数时经常被误解的4个重要统计概念。这些包括生存分析和逻辑回归的相似性、构建损伤风险逐点置信区间的正确尺度、辨别哪种形式的损伤风险函数最优的能力以及对同一受试者重复测试的处理。
通过模拟和对基础数学的研究来探索统计模型。
我们为单预测变量损伤风险函数的统计学有效构建和正确解释提供建议。
本文旨在提供有用且易懂的统计指导，以改进构建损伤风险函数的实践。
