Category Archives: Confidence intervals

2. Why do we compute p-values?

In my previous blog I said that the p-value, which test the null hypothesis, is a near meaningless concept.  This was based on: In nature, the likelihood that the difference between two different treatments will be exactly any number (e.g., … Continue reading

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3. Meaningful ways to determine the adequacy of a treatment effect when you have an intuitive knowledge of the dependent variable

“A theory has only the alternative of being wrong. A model has a third possibility – it might be right but irrelevant.” Manfred Eigen In my last stats course I was amazed to hear my teacher announce that If we … Continue reading

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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, Non-Inferiority, non-inferiority hypothesis, noninferiority hypothesis, Not worse than | Tagged , , , , , , | Leave a comment

12. Significant p-values 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 sub-sections is for Statistical Consultants.  A short time ago, there were over fifty comments on the topic of ‘Does … Continue reading

Posted in assumptions, Confidence intervals, Effect Size, p-values, Treatment Effect | 83 Comments

22. A question on QoL, Percentage Change from Baseline, and Compassionate-Usage 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

Posted in Confidence intervals, Design, Interval, Nominal, Ordinal, percentage change from baseline, Statistics, Treatment Effect | 4 Comments

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

Posted in assumptions, Confidence intervals, Design, Effect Size, non-parametric statistics, Ordinal, p-values, Parallel Group, Power, t-test, Treatment Effect | 1 Comment

31. Case History of a Trial

A colleague asked me to review a trial.  I will mask the identity of the trial and obfuscate irrelevant details, like the disease, timing, treatment, and key parameter. The patients had abnormal parathyroid glans, with hypercalcemia.  This was a Phase … Continue reading

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