What does "Power Prior" mean?
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The power prior is a way to use past data to inform current analyses. It works by adjusting how much we trust historical data when making predictions. This adjustment is done using a special number, known as a discounting parameter, which can change based on different factors.
Normalized Power Prior
When the discounting parameter is treated as random, we call it the normalized power prior. This approach allows for more flexibility in how historical data is used, especially when the past and present data might not match perfectly.
Importance in Modeling
The power prior is useful in various statistical models, especially when combining information from different datasets. By looking at historical data along with new data, analysts can make better predictions and decisions.
Optimal Priors
To get the best results from the power prior, researchers look for the best settings for the discounting parameter. They aim to use historical data effectively when it is relevant but limit its influence when the data do not fit well together. This balance helps ensure that the findings are as accurate and trustworthy as possible.