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Optional stopping: no problem for Bayesians.

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    This summary is machine-generated.

    Optional stopping, or peeking at data during an experiment, is not problematic for Bayesian inference with Bayes factors. Bayesian interpretations remain valid regardless of the stopping rule used.

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    Area of Science:

    • Statistics
    • Bayesian Inference
    • Experimental Design

    Background:

    • Optional stopping, or sequential analysis, involves deciding to continue or stop an experiment based on accumulating data.
    • This practice inflates Type I error rates in frequentist significance testing.
    • Recent studies have questioned whether optional stopping also poses issues for Bayesian inference using Bayes factors.

    Purpose of the Study:

    • To investigate whether optional stopping affects the validity of Bayesian inference when using Bayes factors.
    • To clarify the interpretation of Bayesian quantities in the context of sequential data analysis.

    Main Methods:

    • The study employed computer simulations to analyze the impact of optional stopping on Bayesian inference.
    • Bayes factors were used as the primary metric for evaluating evidence.

    Main Results:

    • Simulation results demonstrated that the interpretation of Bayesian quantities, specifically Bayes factors, is independent of the stopping rule.
    • Optional stopping does not inherently invalidate Bayesian analyses or conclusions.

    Conclusions:

    • Researchers can confidently use optional stopping in their experimental designs when employing Bayesian methods.
    • Bayesian analysis of data, irrespective of the stopping rule, provides valid measures of subjective belief and evidence for theoretical positions.