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SaltZookeepergame691 t1_jedqrno wrote

Reply to comment by CaptainHindsight92 in Sublingual Spray With THC And CBD Can Control Blood Sugar, Lowers Cholesterol In Type 2 Diabetes Patients by Defiant_Race_7544

Given their first table reveals fatal mistakes in their basic statistics and randomisation process, I’m with ya ;)

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OB1_error t1_jeepnv2 wrote

Could you elaborate? The data in table 1 looks ok to me, but I’m no statistician.

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SaltZookeepergame691 t1_jeexi7n wrote

Table 1 is all over the place, which is my point.

Running t-tests on the continuous variables gives very highly significant differences for age, cholesterol, TAGs, HDL, LDL, HbA1c, a small significant difference for BMI, and nearly significant for creatine and insulin.

Take age, the very first item in the table, which is reported as p=0.26. But, it's actually p<0.0001!

Yes, I know some could probably usea non-parametric test, but 1) we only have summary data, 2) they don't say what they used for their p value calculations, 3) I get the same as them for two of the variables using t tests.

These extreme p values are not values you expect, at all, in a true randomised trial: either 1) it is not randomised/randomisation failed; 2) it was initially randomised and these massive differences are caused by them excluding n=3 from the placebo group and n=1 from the intervention group for this table, in which case the fact they've done their analysis in the PP analysis in such clearly different populations makes it not worth bothering with nad not randomised; 3) something more nefarious.

By my reckoning, the only p values for continuous variables that are correct in table 1 are HOMA2-IR and fasting glucose!

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joxeloj t1_jegaunh wrote

You're correct that many of the p-values are off. Even some of their Fisher Exact tests are off (e.g. I get p=0.47 for hypertension). I think they probably used Mann-Whitney U tests after a Shapiro-Wilk's p<0.05 for many of these, but I can't prove that without access to their data. It is odd overall.

I will point out they claim to test their primary hypothesis by ANCOVA accounting for baseline values, and randomization is not necessarily pointless even if you don't end up with well-balanced groups by specific endpoints. With that said you could probably get a response published on the basis of some of these discrepancies.

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