anciendaze
Senior Member
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I would agree, if I thought the numbers had any significance.I see. I'm pretty sure the right figures to use - in terms of statistical validity - are the ones comparing the difference in gains between baseline and 52 weeks, not the difference in values 52 weeks.
Unfortunately, measures of statistical significance used here depend on accurate values for parameters describing a particular distribution. That distribution has known characteristics: 1) it is symmetrical; 2) mean, median and mode are very close together; 3) a predictably small number of outliers exceed a given number of standard deviations from the mean. None of these characteristics is true for the population used to establish "normal" as defined by this study. Some gross departures are readily apparent.
One measure of the validity of an assumed standard deviation is stability in a control group. This also fails here. Standard deviations increased over time. Considering the central role of standard deviation in establishing criteria for "recovery", as well as statistical significance, weakness in this pillar of the statistics slips by with surprisingly little concern voiced by investigators.
The mean value from which deviations should be measured also seems uncertain. If the two parameters carrying all possible information about an assumed distribution are as indefinite as these appear, no confidence in calculated values is warranted.
What the numbers released show is a heterogeneous cohort created by entry requirements dispersing over time. Random walk models would show similar changes.
Selection effects are apparent at multiple stages. Roughly half those they attempted to enroll declined. Classic values for bias created by dropouts are hidden by treating those who did not complete the only objective measure presented at the end of the trial as though they fully completed. Data from Actometers was simply dropped. With some 30% of those 'completing' having no objective data whatsoever for improvement, plus dispersal of a meaningless cohort, there should be no problem getting numbers in the range claimed as "moderate improvement".
Lack of selection shows up in one area, adverse events. There were more than 3,000 adverse events distributed over 600 participants. Any drug trial with this rate of adverse events would be halted. An attempt to redefine adverse events during a trial, to make them less likely, as was done here, will typically get you investigated. We are told few were "serious adverse events" based on review by three independent assessors who turn out to be less than independent.
Acceptance of this study by a medical establishment does more to undermine confidence in mainstream medicine than to validate the results. If medical professionals can't tell when they are getting bamboozled, great savings are possible in funding medical research. Legislators take note.