Biostatistics & Research · patient case question
What does a Type II error represent?
Patient case: Patient who refuses whitening because of a cancer claim
Patient: Female, 38 years old
Chief Complaint: Interested in tooth whitening but has read online that it causes cancer.
Background: She raises the concern at consultation. The clinician wishes to find the best available evidence on whether vital tooth whitening is associated with oral cancer risk, in order to counsel her properly.
Current Findings: No relevant medical history. Generalised extrinsic staining. Sound dentition.
Show answer and explanation
Correct answer: D. Failing to detect a difference that genuinely exists (a false negative)
- A. That describes a Type I error (alpha) — a FALSE POSITIVE, rejecting a true null hypothesis. Alpha is conventionally set at 0.05.
- B. Inaccurate measurement is measurement or information bias, again a different category of problem.
- C. Unrepresentative sampling is selection bias, a threat to external validity, not a hypothesis-testing error.
- D. CORRECT. A Type II error (beta) is a FALSE NEGATIVE — the null hypothesis is accepted when it is in fact false, so a real effect is missed. The commonest cause is inadequate sample size. Statistical power equals 1 minus beta, and studies are conventionally designed for at least 80% power.
Note: Mnemonic: Type I error — you see something that isn't there (false positive, alpha). Type II error — you miss something that is there (false negative, beta).
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