Here goes [General Sta­tis­tics]

posted by PharmCat  – Russia, 2020-07-29 21:11 (696 d 18:32 ago) – Posting: # 21799
Views: 2,001

Hello Maestro, hello all!

As if echoing you... Don't deny right away, at least in an hour... Provocational post :cool:

All thoughts about S2BR, s2BT, s2BTR separately is erroneous or incomplete. This all is part of V. All model notations also explain nothing. You can get some variance component, but without other this nothing matter. This is my very very very humble opinion. But why we need V except to get some specific component for special reason? First of all we need to calculate SE for vector of fixed effect. It can be done simple: sqrt(LCL') where L is "contrast vector" and C is variance-covariance matrix of fixed effect. C can be found like this: SUMi(Xi'Vi-1Xi)-1

There are misunderstanding in mixed models. Many people thoughts, that each line of data is observation. It really is in models without repeating. But in models with repeating all data for each subject is statistically independent observation for multivariate normal random variable with variance-covariance matrix V. V is indivisible and all attempts to obtain components are meaningless, if only because the structure of this matrix itself is just an assumption. If we consider V holistically, then it makes some sense.

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