Investigators conducting new
research often have access to data from previous studies, and in such cases it
is not only scientifically reasonable but also statistically advantageous to
incorporate this information into the current analysis.
Consider, for example,
the common scenario in which a funding agency finances research incrementally,
first requiring a small pilot or feasibility study before funding a more elaborate trial. In such cases, it can be beneficial to incorporate the pilot
data into the subsequent analysis to increase the power to detect treatment effects.
One strategy for synthesizing results across studies is through a Bayesian
modeling approach. Because Bayesian methods can incorporate historical
information through a prior distribution, they provide a natural framework for
updating information across studies.
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