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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 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
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Category Archives: pvalues
1.A Another view on testing by Peter Flom, PhD
The following was written by Peter Flom, PhD dated November 4, 2009 from a Book Review: Statistics as Principled Argument by Robert Abelson. His website is http://www.statisticalanalysisconsulting.com/ His blog is http://www.statisticalanalysisconsulting.com/blog/ I changed the date of publication of 12July2012 to 1Oct2011 … Continue reading
Posted in pvalues, Statistics, Treatment Effect
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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
9. Dichotomization as the Devils Tool
There are two types of people, those who classify people into two types of people and those who don’t. Never trust anyone over thirty. As Mason said to Dixon, ‘you gotta draw the line somewhere’. *** Don’t get me wrong, … Continue reading
Posted in Biostatistics, Dichotomization, Interval, Nominal, Ordinal, pvalues, Power, Statistics
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10. Parametric or nonparametric analysis – Why one is almost useless
… ‘If you lost your watch in that dark alley, why are we looking here?’ ‘Well, <hic> there’s light here.’ (old chestnut) *** In my last blog, I stated that we should avoid dichotomizing as it throws away a lot … Continue reading
12. Significant pvalues in small samples
‘Take two, they’re small’ *** Are the results from small, but statistically significant, studies credible? One of the American Statistical Association’s subsections is for Statistical Consultants. A short time ago, there were over fifty comments on the topic of ‘Does … Continue reading
15. Variance, and ttests, and ANOVA, oh my!
Statistics – a specialty of mathematics whose basic tenant is ‘Exceptions prove the rule’. Mr. McGuire: I just want to say one word to you. Just one word. Benjamin: Yes, sir. Mr. McGuire: Are you listening? Benjamin: Yes, I am. … Continue reading
Posted in ANOVA, pvalues, ttest, Uncategorized, Variance
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19. A Reconsideration of My Biases
No virtual observations were harmed in the running of this study. A man with one watch knows what time it is. A man with two is not sure, at least for the Wilcoxon test. And don’t try this at home, … Continue reading
Posted in ANOVA, Effect Size, nonnormality, nonparametric statistics, pvalues, Power, ttest
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23. Small N study to publish or not?
The following question was sent to me, I thought it useful enough for a full elaboration: Submitted on 2014/05/12 at 8:23 am Dr. Fleishman, I am so happy I found your site. I have been trying to decide how to best … Continue reading
29. Should you publish a nonsignificant result?
53. If the beautiful princess that I capture says “I’ll never marry you! Never, do you hear me, NEVER!!!”, I will say “Oh well” and kill her. 61. If my advisors ask “Why are you risking everything on such a … Continue reading
Posted in Effect Size, pvalues, Power, Psychology, Statistics, Treatment Effect
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