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Efficiency in sequential testing: Comparing the sequential probability ratio test and the sequential Bayes factor

Angelika M Stefan1, Felix D Schönbrodt2, Nathan J Evans3

  • 1Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands. a.m.stefan@uva.nl.

Behavior Research Methods
|March 2, 2022
PubMed
Summary
This summary is machine-generated.

Sequential Probability Ratio Test (SPRT) and Sequential Bayes Factor Test (SBFT) are compared for psychological research. Both methods share similarities within a unified framework, with efficiency depending on model specification and population truth.

Keywords:
Bayes factor design analysisBayesian inferenceDesign optimizationExperimental designHypothesis testingLikelihood testsSample size determinationStatistical error control

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Area of Science:

  • Psychological research methodology
  • Statistical inference
  • Sequential hypothesis testing

Background:

  • Sequential hypothesis testing allows for early termination of data collection once sufficient evidence is gathered.
  • Two prominent sequential methods, the Sequential Probability Ratio Test (SPRT) and the Sequential Bayes Factor Test (SBFT), are increasingly used in psychological research.

Purpose of the Study:

  • To compare the Sequential Probability Ratio Test (SPRT) and the Sequential Bayes Factor Test (SBFT) in the context of psychological research.
  • To elucidate the similarities and differences between SPRT and SBFT, particularly their underlying mechanisms for evidence monitoring and error control.
  • To provide guidance on selecting appropriate sequential designs by balancing efficiency, robustness, and uncertainty quantification.

Main Methods:

  • Comparative analysis of SPRT and SBFT, highlighting their shared mathematical framework and philosophical underpinnings.
  • Examination of evidence monitoring and error control mechanisms within both sequential testing procedures.
  • Simulation studies to assess the efficiency of SPRT and SBFT under varying statistical model specifications and population truths.

Main Results:

  • SPRT and SBFT, despite different origins, can be viewed as instances of a unified sequential hypothesis testing framework.
  • Both methods employ similar strategies for monitoring accumulating evidence and controlling decision errors.
  • The relative efficiency of SPRT and SBFT is contingent upon the precise statistical models used and the true state of the population.

Conclusions:

  • Researchers designing sequential studies must carefully consider the trade-offs between test efficiency, robustness to model misspecification, and accurate quantification of uncertainty.
  • Guidance is offered for making informed design decisions in sequential hypothesis testing, tailored to specific research needs and preferences.
  • The unified framework provides a valuable perspective for understanding and applying diverse sequential testing procedures in psychological science.