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Biostatistics Flashcards

7 cards from real FPGEE practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

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  1. A meta-analysis reports an I² statistic of 75%. How should this be interpreted?

    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.

  2. Which statistical test is most appropriate to compare median survival times between two independent treatment groups when data are censored?

    Answer: Log-rank test

    The log-rank test is specifically designed to compare survival distributions between groups while accounting for censored data.

  3. In a crossover clinical trial, what is the primary statistical concern that must be addressed?

    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.

  4. A drug reduces the absolute risk of myocardial infarction from 4% to 1%. What is the relative risk reduction?

    Answer: 75%

    RRR = (Control risk − Treatment risk) / Control risk = (4% − 1%) / 4% = 75%.

  5. Which of the following best describes a Type II error in hypothesis testing?

    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.

  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?

    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.

  7. In Kaplan-Meier survival analysis, what does a steeper drop in the survival curve at an early time point indicate?

    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.