True or False: The greatest benefit of a logistic regression model with the outcome of ln(probability of disease/(1-probability of disease)) is that it is the most direct way to calculate a cumulative incidence difference.

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BlackTom AI · Accepted Answer

Here are the considerations for each answer option, presented with varied framing to help understanding.
Option 1: 'True' — This statement claims that the greatest benefit of a logistic regression model, whose outcome is the log odds ln(p/(1-p)), is that it is the most direct way to calculate a cumulative incidence difference. The key issue is that logistic regression targets odds, not probabilities directly. The model provides log-odds and odds ratios, which describe relative associations, not absolute risk differences. Cumulative incidence difference (risk difference) requires differences in probabilities between groups, which are not directly given by the logistic link function. In practice, one would need to transform predicted probabilities and then subtract them, or use alternative modeling approaches (e.g., log-binomial or Poisson regression with robust standard errors) to estimate risk differences more directly. Therefore, the claim that logistic regression is the most direct way to obtain a cumulative incidence difference is not accurate.
Option 2: 'False' — This choice recognizes that the stated benefit is not correct. Since logistic regression focuses on modeling log-odds and yields odds ratios, its direct outputs are not probabilities or risk differences. While you can compute predicted probabilities from a logistic model and then compute a risk difference post hoc, that is an extra step and not a direct, built-in feature of the logistic regression framework. Moreover, estimating cumulative incidence differences often benefits from models that target probabilities on the original scale or link functions appropriate for risk differences, rather than relying on odds. Consequently, this option correctly identifies the misconception in the claim.
In summary, the assertion in option 1 is misleading because logistic regression is oriented toward odds and odds ratios rather than a direct, built-in calculation of cumulative incidence differences, and option 2 correctly points out that distinction by marking the statement as false.

EPI 202 Week 5: Self Assessment: Logistic Regression

True or False: The greatest benefit of a logistic regression model with the outcome of ln(probability of disease/(1-probability of disease)) is that it is the most direct way to calculate a cumulative incidence difference.

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