Bioequivalence and Bioavailability Forum

Dear Bears, dear Rusers, dear all,

recent I (The power to know is with me) had the opportunity to take a deeper look on to R and into the source code of bear.

Since I am a novice in R I could not fully understand all the lot of code. But I argue that the 90% confidence interval is calculated in BANOVA.r (the part of bear which deals with the SAS GLM counterpart) but in a different manner.

My interpretation of the code is: The MSE is taken from the lm() call, but point estimate is calculated by the ordinary means m_T and m_R.
Any body out there: Am I right?

If I am right: This is ok, as long as the design is balanced between sequences. but for unbalanced data there is a difference

In SAS this is done usually via LSMeans or an ESTIMATE statement.

Astonishing enough there seems no counterpart to LSMeans in R. After reading tons of Web pages it seems this another mine field like Type III sums of squares.

But nevertheless there is the task to estimate the treatment effect with 90% confidence interval (from the parameter of the fitted model), i.e. from a counterpart of the ESTIMATE statement.

Dear Bears have a look on to this page. Eventually this helps you. I don't understand it, because I am a novice .