Braveheart! [🇷 for BE/BA]

posted by ElMaestro  – Denmark, 2020-07-13 12:13 (1750 d 08:39 ago) – Posting: # 21681
Views: 25,405

Hi all,

The solution I posted is a total winner. :-D:-D:-D Where do I collect my medal? :-D:-D:-D

Will be happy to learn of performance on other datasets, in particular of differences between results or non-convergence (which is often something related to instability caused by the initial guess being too far from the optimum). Obviously, with this implementation the input format has to meet the expectation of the algo. For example, T and R coded as T and R, not A and B, in this implementation. All this is unrelated to the task of this thread and can be rather easily worked out as well.

A slight change this morning, for the initial guesses, less clumsy and more likely (in the nonrestricted fashion ;-) ) to reflect the optimal solution:

Some.Initial.Guesses=function(foo)
{
 #guess varT
 D1=subset(D, (D$Trt=="T"))
 m=lm(log(Y)~factor(Seq)+factor(Per)   , data=D1)
 varT=anova(m)["Residuals", "Mean Sq"]
 
 #guess VarWR
 D1=subset(D, (D$Trt=="R"))
 m=lm(log(Y)~factor(Seq)+factor(Per)+factor(Subj)  , data=D1)
 varWR=anova(m)["Residuals", "Mean Sq"] 

 #guess varBR
 D1=subset(D, (D$Trt=="R"))
 m=lm(log(Y)~factor(Seq)+factor(Per)   , data=D1)
 varBR=anova(m)["Residuals", "Mean Sq"] - varWR

 #guess varRT (between), must tbe closer to the other two betweens.
 ##perhaps mean is a decent guess.
 varRT=0.5*(varT+varBR)

 rslt=c(varT, varBR, varWR, varRT)
 return(rslt)
}
—
Pass or fail!
ElMaestro

Complete thread:

UA Flag
Activity
 Admin contact
23,424 posts in 4,927 threads, 1,673 registered users;
95 visitors (0 registered, 95 guests [including 1 identified bots]).
Forum time: 20:53 CEST (Europe/Vienna)

There are two possible outcomes: if the result confirms the
hypothesis, then you’ve made a measurement. If the result is
contrary to the hypothesis, then you’ve made a discovery.    Enrico Fermi

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5