The ability to answer this question is crucial for medical rehabilitation. Dozens of rehabilitations interventions continue to be used despite the the lack of evidence showing treatment efficacy. Bayesian methods allow the explicit incorporation of a priori information, biases, and clinical intuition in data analysis while, at the same time, provide a method for overturning or modifying these biases when evidence is to the contrary. Bayesian methods are particularly useful in meta-analysis where evidence from many studies needs to be integrated for interpretation. Bayesian methods are well designed for monitoring data as they accumulate during a trial to assist in determining the appropriateness of terminating a trial when the preliminary data show a clear benefit or, conversely, a detrimental effect.
Bayesian analysis can be computer intensive.
We are seeing more computational software becoming available to perform Bayesian analysis now that powerful and inexpensive computers are widely available. Another factor that has contibuted to the an under utilization of Bayesian methods is that relatively few statisticians are proficient in the routine application of Bayesian analysis. Again, we are seeing that trend change. All rights reserved.