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Zorluk: OrtaStatistical Inference and Hypothesis Testing

An academic medical center conducts a single-center randomized controlled trial comparing a novel wound closure method to standard suturing in patients undergoing exploratory laparotomy. The primary outcome is the incidence of surgical site infection within 3030 days. The trial enrolls 120120 patients, with 6060 randomly assigned to each group. The results demonstrate a 3030-day infection rate of 8.3%8.3\% in the novel closure group and 15.0%15.0\% in the standard suturing group. The corresponding relative risk (RR) is 0.550.55, with a 95%95\% confidence interval (CI) of 0.200.20 to 1.511.51 and a p-value of 0.280.28. Based on these findings, the hospital committee decides against adopting the novel method, citing that it is definitively not effective. Which of the following is the most accurate statistical evaluation of this trial's results and the committee's conclusion?

  1. The trial likely lacks sufficient statistical power, and the committee's decision may represent a Type II error.Cevap
  2. B
    The confidence interval crossing the null value confirms the novel method acts as a confounding variable.
  3. C
    The retrospective nature of patient enrollment inherently invalidates the calculated relative risk.
  4. D
    The p-value of 0.280.28 indicates a 28%28\% probability that the novel method altered the positive predictive value of the diagnosis.
  5. E
    The findings indicate a need to routinely administer broad-spectrum antibiotics to achieve statistical significance.

Cevap

The trial likely lacks sufficient statistical power, and the committee's decision may represent a Type II error.
The correct answer identifies that the study is likely underpowered. Statistical power is the probability of correctly rejecting a false null hypothesis. Power is heavily dependent on the sample size and the number of events. In this trial, despite observing a clinically meaningful 45%45\% relative risk reduction (RR=0.55RR = 0.55), the confidence interval is very wide (0.200.20 to 1.511.51) because the sample size (n=120n=120) is small. When an underpowered study fails to reach statistical significance (p=0.28p = 0.28), one cannot definitively conclude the intervention is ineffective. Concluding 'no effect' under these circumstances exposes the investigators to a high risk of a Type II error (failing to detect a true difference).

Adım Adım Çözüm

1
Analyze the point estimate and statistical findings.
The relative risk is 0.550.55 (suggesting a substantial 45%45\% reduction in infections), but the 95%95\% CI (0.20−1.510.20-1.51) crosses 1.01.0 and p>0.05p > 0.05.
This establishes that the results are not statistically significant, but the point estimate is clinically meaningful.
2
Evaluate the sample size and study power.
The trial enrolled only 120120 patients with low event rates (8.3%8.3\% and 15.0%15.0\%).
Small sample sizes lead to wide confidence intervals and low statistical power, meaning the study may not be able to detect a true difference even if one exists.
3
Determine the type of statistical error risking the committee's conclusion.
Concluding 'no difference' based on a non-significant p-value in an underpowered study is risking a Type II error.
A Type II error (false negative) occurs when a study fails to reject the null hypothesis when it is actually false.

Anahtar Kavram

In underpowered studies, a lack of statistical significance (p>0.05p > 0.05) does not prove the absence of an effect; concluding so risks a Type II (beta) error.
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