Biostatistics
A research team is designing an RCT to compare a new bone graft substitute versus autograft for spinal fusion. The primary outcome is fusion rate at 12 months. The sample size calculation requires decisions about acceptable error rates. The statistician explains that they need to balance the risk of false positive findings against the risk of missing a true difference. Regarding Type I and Type II errors in clinical research:
Mark each as TRUE or FALSE
Type I error (alpha, α) is a FALSE POSITIVE - rejecting the null hypothesis when it is actually true...
Type II error (beta, β) is a FALSE NEGATIVE - failing to reject the null hypothesis when it is actua...
Type I error is a false negative (missing a true effect); Type II error is a false positive (finding...
The relationship between alpha and beta involves trade-offs: lowering alpha (being more stringent ab...
Multiple comparisons increase the family-wise Type I error rate: with 20 independent tests at α=0.05...
Answer the questions to see explanations
Click T (True) or F (False) for each option