Main Site
Search

Recent Posts
 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
Categories
Stat comments and Questions
 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
 Allen Fleishman on 12. Significant pvalues in small samples
 Omar Farooque on 12. Significant pvalues in small samples
RSS Feeds
Category Archives: noninferiority hypothesis
5. Accepting the null hypothesis
“All models are wrong. … But some are useful.” George Box *** In my first blog I stated a truism, that was hopefully taught in your first statistics class: You can’t accept the null hypothesis. You can ONLY reject the … Continue reading
Posted in Biostatistics, Confidence intervals, NonInferiority, noninferiority hypothesis, noninferiority hypothesis, Not worse than
Tagged confidence intervals, inferiority hypothesis, inferiority testing, noninferiority, noninferiority, not worse than, proving the null hypothesis
Leave a comment
8. What is a Power Analysis?
People who haven’t the time to do things ‘perfectly’, always have time to do them over. Measure once, cut twice. Measure twice, cut once. ‘My god, you’ve conclusively proven it. Time equals Money.’ *** Cost for Failure Every CEO I’ve … Continue reading