LSMeans [General Statistics]
I am a bit backward.
Once again I would like to raise the wonderful topic of LSMeans.
They are a SAS invention and I am still not sure I have truly understood what the hell they really are. Or more correctly, I am very sure I have no clue whatsoever about them.
Now, before someone throws a handful of web pages at me, I want to assure you, I have read them already. I am posting this because I still don't get it after all that reading e.g. here, here , and here.
The recent question about baseline adjustment and covariates in this forum made me try to understand LSMeans again. So I have been sleepless since then, of course. Shouldn't have done it. But that's hindsight.
For example: "When covariates are present in the model, the LSMEANS statement produces means which are adjusted for the average value of the specified covariate(s)."
I have no friggin clue what that really means.
Can someone, without using package lsmeans in R or automated tools, explain in slowmotion me what LSMeans really are and how exactly you would go about deriving LSMeans from scratch in a concrete dataset given a model? Feel free to use the code in the thread mentioned above as a starting point, this would ease my understanding.
Edit: Category changed; see also this post #1. [Helmut]
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- LSMeans - ElMaestro, 2018-02-27 09:02 [General Statistics]
- Understanding (!) LSMeans - d_labes, 2018-02-28 09:49
- Huge gap in my understanding - ElMaestro, 2018-03-04 10:03