ANOVA fixed and random effects [General Sta­tis­tics]

posted by ElMaestro  – Denmark, 2019-02-08 18:00  – Posting: # 19890
Views: 582

Hello to you too, Babe_Ruth :-D


» It's a food effect study where the subject takes the study drug under fasted conditions, 14-day washout, then takes study drug under fed conditions. The proposed is ANOVA model is to analyze log-transformed Cmax and AUClast with terms for treatment condition (Fasted and Fed) as a fixed effect and subject as a random effect.

» Is this appropriate, and why or why not?

That might do, but why not crossover? You'd gain information or at least have an opportunity to impress an agency with design complications :-) and you'd potentially have less deficiency letters.

» Compared to the standard 2x2 crossover study, what are the limitations of the above study design in terms of assessing inter- and intra-subject variability?

If you do it your way, then the most straightforward evaluation is a (paired) t-test approach or equivalently a linear model with two fixed effect (Condition, subject). It will give the exact same result.

There are situations when you'd be having an advantage of the true crossover. For example, imagine there were a tolerability issue, such as metformin IR in fasted naïve subjects who get gastric upsets. You'd potentially see it already in period 1 in a crossover because half the subjects will be fasted then. And so forth.

In both cases you can argue that the model residual (or pooled variance, in case of t-test) is a measure of intra-subject variability. In both cases you will be able to extract also a quantity for total variability observed between subjects. For Feinschmeckers, the latter may not always be rightfully called the between-subject variability since it has components of both within and between whichever way you measure it. But this is also a bit about semantics and personal preferences and habits.
The crossover gives you also info about period and sequence effects which for all practical purposes might (or might not) be of interest to the person assessing it. A between-period time of 14days should suffice in most cases, no doubt about it, at least in terms of he food phenomena, and hopefully also for the elimination of the drug.

if (3) 4

x=c("Foo", "Bar")
b=data.frame(x)
typeof(b[,1]) ##aha, integer?
b[,1]+1 ##then let me add 1


Best regards,
ElMaestro

“(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures.” New York Times (ed.), June 9, 2018.

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