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When testing the efficacy of a potential medical treatment, researchers compare subjects who received the treatment against subjects who received a {{w|placebo}}. Usually each subject does not know whether they received the treatment or placebo, and neither do the practitioners, until the end of the trial. This distinguishes the actual effects of the treatment from the effects of simply participating in a study. People who receive a placebo (or an ineffective treatment) often believe their treatment is working due to such causes as paying more attention to one's health or expecting to feel better. This misattribution of effect to a non-treatment is called the "placebo effect".
 
When testing the efficacy of a potential medical treatment, researchers compare subjects who received the treatment against subjects who received a {{w|placebo}}. Usually each subject does not know whether they received the treatment or placebo, and neither do the practitioners, until the end of the trial. This distinguishes the actual effects of the treatment from the effects of simply participating in a study. People who receive a placebo (or an ineffective treatment) often believe their treatment is working due to such causes as paying more attention to one's health or expecting to feel better. This misattribution of effect to a non-treatment is called the "placebo effect".
  
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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).  
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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 show 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).  
  
 
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.
 
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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