American Board of Surgery Qualifying Exam (ABS QE) Practice Test

Which situation exemplifies a Type I error?

1. Believing there is no difference when one exists

2. Assuming a drug is effective when it is not

3. Correctly identifying the absence of an effect

4. Missed identification of a treatment's efficacy when present

The correct answer is: Assuming a drug is effective when it is not

A Type I error, also known as a false positive, occurs when a null hypothesis is incorrectly rejected when it is actually true. This means that the situation indicates that there is an effect or difference (for instance, assuming a drug is effective) when in reality there is none. In this context, the situation of believing a drug is effective when it is not, clearly exemplifies a Type I error. The assertion that a treatment produces a positive result leads to potentially misleading conclusions and unnecessary clinical decisions based on false information. The other scenarios don't align with the definition of a Type I error. For example, believing there is no difference when one exists represents a Type II error, where a true effect is missed. Identifying the absence of an effect correctly demonstrates accurate hypothesis testing, and missed identification of a treatment's efficacy when it is actually present also describes a Type II error situation. Understanding these distinctions is crucial for interpreting statistical outcomes in clinical research accurately.