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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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Stat comments and Questions
 Allen Fleishman on 22. A question on QoL, Percentage Change from Baseline, and CompassionateUsage Protocols
 Kate on 22. A question on QoL, Percentage Change from Baseline, and CompassionateUsage Protocols
 Allen Fleishman on 24. Simple, but SimpleMinded
 Victor Levenson on 24. Simple, but SimpleMinded
 Allen Fleishman on 24. Simple, but SimpleMinded
 Victor Levenson on 24. Simple, but SimpleMinded
 Allen Fleishman on 12. Significant pvalues in small samples
 Merm on 12. Significant pvalues in small samples
 Allen Fleishman on 12. Significant pvalues in small samples
 Phil Assheton on 12. Significant pvalues in small samples
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Category Archives: Statistical Analysis Plan
6. ‘Lies, Damned Lies, and Statistics’ part 1, and Analysis Plans, an essential tool
Lies, Damn Lies, and Statistics Let me start this blog with one of my pet peeves. I abhor the quote ‘Lies, Damn Lies, and Statistics’. For me, a statistician, it has as much truth as saying that ‘the earth is … Continue reading
11. pvalues by the Pound
‘Failure is always an option’ – Myth Busters ‘The Statistician is in. 5¢ per pvalue.’ ‘Your statistical report is being delivered by three UPS trucks.’ ‘It takes three weeks to prepare a good adlib speech.’ – Mark Twain *** Let … Continue reading