Abstract
Double blind tests of drugs and procedures depend on obtaining two equal and randomly assigned groups to be compared. With a diagnosis based only on symptoms, but with different etiologies, this is not very likely. We here show the probability of obtaining two equal groups with one diagnosis but three etiologies. The mathematical name for such a problem is multivariate hypergeometric distribution. We find that increasing the group size decreases the probability.
Highlights
Assigned double blind is the gold standard for therapeutic interventions and procedures in medicine
We have tried to calculate the chance that a group of patients divided into two groups randomly assigned would be equal, if three different etiologies were subsumed under the same diagnosis
It is clear that with different etiologies subsumed under one diagnosis, the random distribution into two equal groups is improbable. It is clear from the calculations done that increasing the numbers, decreases the probability of getting two equal groups with the same distribution
Summary
Assigned double blind is the gold standard for therapeutic interventions and procedures in medicine. One of the conditions for using this method is that the two compared, randomly assigned groups are equal. Many diagnoses are symptom based, and there is every possibility that a diagnostic entity may have several different causes. We have tried to calculate the chance that a group of patients divided into two groups randomly assigned would be equal, if three different etiologies were subsumed under the same diagnosis.
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