ACRP Biostatistics and Data Analysis Flashcards
6 cards from real ACRP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 ACRP Biostatistics and Data Analysis flashcards as text
What is the role of a Data Safety Monitoring Board (DSMB) in a clinical trial?
Answer: To independently monitor accumulating data and recommend stopping or modifying the trial if safety or efficacy criteria are met
A DSMB is an independent committee that periodically reviews unblinded interim data to protect participant safety and ensure trial integrity.
What is a Type I error in statistical testing?
Answer: Concluding that a treatment is effective when it is not (false positive)
A Type I error (alpha error) occurs when the null hypothesis is rejected incorrectly, falsely concluding that an ineffective treatment works.
What is stratified randomization and when is it used?
Answer: Randomization that ensures balance of key prognostic factors (e.g., age, disease severity) across treatment groups
Stratified randomization controls for important baseline variables by ensuring they are equally distributed between treatment arms, improving comparability.
What is the primary purpose of a statistical analysis plan (SAP) in a clinical trial?
Answer: To pre-specify all statistical methods and analyses before data unblinding to prevent bias
The SAP documents all planned analyses before unblinding, ensuring results are not influenced by knowledge of outcome data (post-hoc analysis bias).
What does 'multiplicity' refer to in clinical trial statistics?
Answer: The inflation of the Type I error rate when performing multiple statistical tests
When multiple endpoints or comparisons are tested, the probability of at least one false positive increases; multiplicity adjustments (e.g., Bonferroni) control this inflation.
What is the Kaplan-Meier method used for in clinical research?
Answer: Estimating survival or time-to-event probabilities from censored data
The Kaplan-Meier method produces survival curves that estimate the probability of an event (e.g., death, relapse) over time, accounting for participants who leave the study early.
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