FPGEE Biostatistics 3 — Questions and Answers
Question 1: A meta-analysis reports an I² statistic of 75%. How should this be interpreted?
- 75% of studies found the treatment effective
- 75% of the variance in effect sizes is due to heterogeneity rather than chance (Correct answer)
- The pooled effect size is 0.75
- 75% of studies had a low risk of bias
Correct answer: 75% of the variance in effect sizes is due to heterogeneity rather than chance
I² quantifies the proportion of total variability in effect estimates attributable to heterogeneity across studies rather than sampling error.
Question 2: Which statistical test is most appropriate to compare median survival times between two independent treatment groups when data are censored?
- Independent samples t-test
- Mann-Whitney U test
- Log-rank test (Correct answer)
- Chi-square test
Correct answer: Log-rank test
The log-rank test is specifically designed to compare survival distributions between groups while accounting for censored data.
Question 3: In a crossover clinical trial, what is the primary statistical concern that must be addressed?
- Observer bias
- Carryover effects from the first treatment period (Correct answer)
- Allocation concealment failure
- Loss to follow-up
Correct answer: Carryover effects from the first treatment period
Carryover (residual) effects occur when treatment from period 1 influences outcomes in period 2, violating the independence assumption.
Question 4: A drug reduces the absolute risk of myocardial infarction from 4% to 1%. What is the relative risk reduction?
- 3%
- 25%
- 75% (Correct answer)
- 400%
Correct answer: 75%
RRR = (Control risk − Treatment risk) / Control risk = (4% − 1%) / 4% = 75%.
Question 5: Which of the following best describes a Type II error in hypothesis testing?
- Rejecting a true null hypothesis
- Failing to reject a false null hypothesis (Correct answer)
- Setting alpha too high
- Using a two-tailed instead of one-tailed test
Correct answer: Failing to reject a false null hypothesis
A Type II error (β) is the failure to reject a false null hypothesis — concluding no effect exists when one actually does.
Question 6: A researcher reports a statistically significant result (p = 0.04) with a very large sample (n = 50,000). What additional information is most critical to evaluate clinical relevance?
- The confidence interval width
- The effect size or clinical magnitude (Correct answer)
- Whether a one-tailed test was used
- The degrees of freedom
Correct answer: The effect size or clinical magnitude
With very large samples, even trivially small differences become statistically significant; effect size determines whether findings are clinically meaningful.
Question 7: In Kaplan-Meier survival analysis, what does a steeper drop in the survival curve at an early time point indicate?
- More censored observations at that time
- A higher rate of the event occurring early in follow-up (Correct answer)
- Greater survival probability at that time
- A larger standard error
Correct answer: A higher rate of the event occurring early in follow-up
A steep drop in a KM curve at any point indicates that many subjects experienced the event (e.g., death or treatment failure) at that time.
FPGEE Biostatistics 3
A meta-analysis reports an I² statistic of 75%.
How should this be interpreted?