A p of .05 does not automatically mean that 5% of the positive results are 
false positives.  It just means that on any given test (if everything else is 
correctly done) there's a probability of .05 that you're getting a false 
positive.

Add to that the fact that in many pieces of research the obtained p of getting 
those results is far below .05.

In my mind I think of it a lot like the Gamblers' Fallacy.  They're (or should 
be) independent events.

m

--
Marc Carter, PhD
Associate Professor of Psychology
Chair, Department of Behavioral and Health Sciences
College of Arts & Sciences
Baker University
--

From: Michael Burman [mailto:[email protected]]
Sent: Monday, April 02, 2012 9:36 AM
To: Teaching in the Psychological Sciences (TIPS)
Subject: re: [tips] Frequency of Type I errors in published research.










I get a sense that I'm going to regret asking this question, but why wouldn't 
setting the alpha value at .05 result in about 5% false positives in the 
literature?  Are people suggesting that the true false positive rate would be 
lower?  I get why it would be higher (statistical tricks, bias, research short 
cuts, etc), but not why it would be lower.

Mike


-------
Michael A Burman Ph.D.
Assistant Professor
Dept. of Psychology
K-12 Outreach Coordinator for the Neurosciences
University of New England

328 Decary Hall
207-602-2301
[email protected]<mailto:[email protected]>



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