## LSMeans, still causing lots of people headaches [General Sta­tis­tics]

❝ Hellobi ,

❝ thanks for helping towards an understanding.

No harm in trying ❝ I am a bit confused, what is ln[T] in your terminology?

❝ Is it individual measurements, or effects form the b-vector or is it the average on the ln scale?

❝ And what is the starting point for this?

It's the individual measurements.

❝ Also, residuals -once a linear model has been fit to the least squares criterion- sum to zero, right? I got confused when you went from step 4 to 5.

Yeah, that's true, the residuals should sum up to zero. The variance will be the sum of squares of the residuals, in this case, will be greater than zero. I was just trying to show the relationship between the residuals and the difference of the lsmeans. The maths isn't perfect one bit.

❝ ❝ The Model Residual is the variance for the difference of LSMeans between Ln[T] and Ln[R].

❝ Why?

❝ I would think it is the plain uncertainty for an (within-) effect estimate in the b vector when we talk crossovers. Multiply by two and you have the variance of the difference or something like that.

Oh yes! Mutiplying it by two gives the variance of the difference of LSMeans. Hope I have not worsened the headache with my statistically incoherent post .

Regards,

Scopy  Ing. Helmut Schütz 