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In this comic a team of researchers appears to have studied some medical treatment, using a placebo controlled test. They present their findings in which a particular subset of participants (out of at least four distinct groups) shows an apparently significant result. The graph shows that three groupings have results whose error-bars indicate that they might easily have zero (or neutral) true effects, if not negative ones. But, even at the lowest extent of the accepted uncertainty, the fourth stands out as definitively having some degree of positive effect (of whatever kind this particular graph is plotting).  
 
In this comic a team of researchers appears to have studied some medical treatment, using a placebo controlled test. They present their findings in which a particular subset of participants (out of at least four distinct groups) shows an apparently significant result. The graph shows that three groupings have results whose error-bars indicate that they might easily have zero (or neutral) true effects, if not negative ones. But, even at the lowest extent of the accepted uncertainty, the fourth stands out as definitively having some degree of positive effect (of whatever kind this particular graph is plotting).  
  
βˆ’
However, it is revealed that the 'treatment' they were given was also a placebo. Their own study was the subject of a placebo controlled test conducted on their methodology. They were the placebo group, while a different team presumably used the exact same methodology to study the real treatment. Thus, all of this team's findings were due to the placebo effect, or else the trial size and scope allowed a purely statistical 'blip' to occur, instead of there being any real merit to the "treatment". This indicates that their methodology shouldn't be used for any real world applications. This may be a subtle dig at the recent {{w|aducanumab}} Alzheimer's drug trial controversy, where post-hoc reanalysis of one subgroup of patients revealed a surprising result when the overall trial had otherwise failed.
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However, it is revealed that the 'treatment' they were given was also a placebo. Their own study was the subject of a placebo controlled test conducted on their methodology. They were the placebo group, while a different team presumably used the exact same methodology to study the real treatment. Thus, all of this team's findings were due to the placebo effect, or else the trial size and scope allowed a purely statistical 'blip' to occur, instead of there being any real merit to the "treatment". This indicates that their methodology shouldn't be used for any real world applications. This may be a subtle dig at the recent aducanumab Alzheimer's drug trial controversy[https://en.wikipedia.org/wiki/Aducanumab] where post-hoc reanalysis of one subgroup of patients revealed a surprising result when the overall trial had otherwise failed.
  
 
The particular flaw in the methodology appears to be dividing too few subjects into too many sub-groups, allowing a chance cluster of anomalous results to overly influence an apparent result. The researcher did find significance in one sub-group, even though in reality there was no signal, just noise, since it was all placebo groups. This references the same p-hacking problem as [[882: Significant]]. Only in this case the researcher themself is the subject of the real trial.
 
The particular flaw in the methodology appears to be dividing too few subjects into too many sub-groups, allowing a chance cluster of anomalous results to overly influence an apparent result. The researcher did find significance in one sub-group, even though in reality there was no signal, just noise, since it was all placebo groups. This references the same p-hacking problem as [[882: Significant]]. Only in this case the researcher themself is the subject of the real trial.

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