Abstract
Abstract Interim analysis of accumulating data in a clinical trial is now an established practice for ethical and scientific reasons. Repeatedly testing interim data can inflate false positive error rates if not handled appropriately. Group sequential methods are a commonly used frequentist approach to control this error rate. Motivated by experience of clinical trials, the alpha spending function is one way to implement group sequential boundaries that control the type I error rate while allowing flexibility in how many interim analyses are to be conducted and at what times. In this paper, we review the alpha spending function approach, and detail its applicability to a variety of commonly used statistical procedures, including survival and longitudinal methods.
Keywords
InterimFrequentist inferenceInterim analysisFlexibility (engineering)Type I and type II errorsComputer scienceFunction (biology)EconometricsStatisticsClinical trialMedicineMathematicsBayesian probabilityBayesian inference
MeSH Terms
BiasClinical Trials as TopicData InterpretationStatisticalDouble-Blind MethodHumansLongitudinal StudiesMulticenter Studies as TopicMyocardial InfarctionPropranololRandomized Controlled Trials as TopicSurvival Analysis
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Publication Info
- Year
- 1994
- Type
- article
- Volume
- 13
- Issue
- 13-14
- Pages
- 1341-1352
- Citations
- 547
- Access
- Closed
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Cite This
David L. DeMets,
K. K. Gordon Lan
(1994).
Interim analysis: The alpha spending function approach.
Statistics in Medicine
, 13
(13-14)
, 1341-1352.
https://doi.org/10.1002/sim.4780131308
Identifiers
- DOI
- 10.1002/sim.4780131308
- PMID
- 7973215