[[{“value”:”Introduction. Your analysis produces a statistically insignificant estimate. Is it because the effect is negligibly different from zero? Or because your research design does not have sufficient power to achieve statistical significance? Alternatively, you read that “The median statistical power [in empirical economics] is 18%, or less” (Ioannidis et al., 2017) and you wonder if the
The post From Reed and Logchies appeared first on Marginal REVOLUTION.”}]]
Introduction. Your analysis produces a statistically insignificant estimate. Is it because the effect is negligibly different from zero? Or because your research design does not have sufficient power to achieve statistical significance? Alternatively, you read that “The median statistical power [in empirical economics] is 18%, or less” (Ioannidis et al., 2017) and you wonder if the article you are reading also has low statistical power. By the end of this blog, you will be able to easily answer both questions. Without doing any programming.
An Online App. In this post, we show how to calculate statistical power post-estimation for those who are not familiar with R. To do that, we have created a Shiny App that does all the necessarily calculating for the researcher (CLICK HERE).
Here is the link and the full story.
The post From Reed and Logchies appeared first on Marginal REVOLUTION.
Economics, Education, Science, Uncategorized, Web/Tech
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