![]() Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. ![]() We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. Variance computations for functional of absolute risk estimates. Understanding what these measures represent is essential for the accurate interpretation of study results. Risk, which refers to the probability of occurrence of an event or outcome, can be defined in absolute or relative terms. ![]() In the previous article in this series on common pitfalls in statistical analysis, we looked at the difference between risk and odds. Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat ![]()
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