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 BioStatistical Blog
 1. Statistic’s Dirty Little Secret
 1.A Another view on testing by Peter Flom, PhD
 1.B Am I a nattering nabob of negativism?
 2. Why do we compute pvalues?
 3. Meaningful ways to determine the adequacy of a treatment effect when you have an intuitive knowledge of the dependent variable
 4. Meaningful ways to determine the adequacy of a treatment effect when you lack an intuitive knowledge of the dependent variable
 5. Accepting the null hypothesis
 6. ‘Lies, Damned Lies, and Statistics’ part 1, and Analysis Plans, an essential tool
 7. Assumptions of Statistical Tests
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Category Archives: percentage change from baseline
18. Percentage Change from Baseline – Great or Poor?
Everything should be made as simple as possible, but no simpler. – Attributed to Albert Einstein *** In my third and forth blog I addressed useful ways to present the results of an analysis. Of course, pvalues wasn’t it. I … Continue reading
22. A question on QoL, Percentage Change from Baseline, and CompassionateUsage Protocols
Yesterday was 1 degree Fahrenheit and today is 10. I’m ten times warmer!! Compassion? We statisticians have evolved beyond such petty human affects. I received the following question from Simon Wilkinson from New Zealand: Dear Allen. To set the scene, … Continue reading
24. Simple, but SimpleMinded
Science is organized common sense where many a beautiful theory was killed by an ugly fact. – Thomas Huxley It really is a nice theory. The only defect I can think it has is probably common to all philosophical theories. … Continue reading
18.1 Percentage Change – Right Way and a Wrong Way
Eat s**t, 300 trillion flies can’t be wrong. [old joke punchline] “No, I dropped them in that dark alley, but I’d never find them there. That’s why we’re looking under the light post.” *** I came across a recent rant … Continue reading
Posted in Effect Size, percentage change from baseline
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