Bioequivalence and Bioavailability Forum

Hi GM,

❝ […] fixed effects used in general crossover studies and possible reasons for significant results of these fixed effects, I didn't found any relevant reasons for the significant group effect.

The p-value tells you only how likely something occurs. If you set your limit to 0.05 that means that you consider a p-value <0.05 denoting an effect which occurred not by pure chance. The reason for an effect is beyond the reach of statistics.
Think about the subject-term. It is always highly significant.* Recode the common effects to something neutral (say, response → Y, sequence → a, subject → b, period → c, treatment → d ) and provide the data to a statistician without telling the background to evaluate the linear model $$\ln(Y) \sim a+b+c+d$$ or – if you insist on the stupid over-specified one given in the guidelines – $$\ln(Y) \sim a+b(a)+c+d$$ Hey, \(p(b)\) or \(p(b(a)) = 0.00000314\). Now ask for a “reason”.
Answer:

Science is wonderfully equipped to answer the question “How?”
but it gets terribly confused when you ask the question “Why?”   Erwin Chargaff

Ask a physicist what gravity is. No, not how it is described in physics. You will be surprised.

❝ Anybody know about the possible reasons for significant group effect...?

Chance? IMHO, testing for it is futile (see there).

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• Unless you perform the study in cloned subjects, which would violate an assumption of the model, namely independence. If I would ever see a study with a p-value >0.05 for the subject effect it would ring my alarm bells.

Hello GM,

there are always potential jokers in play:

1. Check if the volunteers within groups have something in common.
Were they recruited in a different manner, in spite of all subjects fulfilling the enrollment criteria? I have seen cases of that recently.
Eyeball if body weight, gender mix, age, or some other factor may differ a bit between groups. If it does then there is a likely -and I am not saying definite- reason, but it is not one associated with a ton of literature.

2. The use of groups is often a capacity issue, relating to the number of beds at the CRO.
Groups are then separated in time, for example by days or weeks, sometimes even months. And time has funky effects, not only on individuals but also on groups of individuals.
Heat wave in Mumbai? Some subjects will be borderline dehydrated when showing up, and they will not feel much like walking around.
Pollen season just set in in Winchester VA? Some subjects will be coughing and wheezing when showing up, even if they don't have a medical history of allergies.
I saw a TV add about vegan diets yesterday. Therefore, brainwashed as I am, the next two weeks I will be buying all the bran and celery soup available in the supermarket and I will be going full tilt into that thing until I realise it is just killing my quality of life, and all the while I will have a changing phenotype of sorts. Until I start living normally again. I find some comfort in knowing that there are others who saw the same TV add and who are suffering the same phenomenon (and the owner of the company selling celery is likely going on monthly vacations to Tonga or some such remote and exotic place, due to victims of his affairs like me, but this is another story).

And so forth.

Finally, bear in mind that phase III studies across centers often have significant center effects. I think this phenomenon is much comparable to the group effect, honestly. Such phase III trials get approved.

The group effect questions from regulators are often not too difficult to handle. They do not become a cause for rejection in my experience.