Transformation to orthogonalize the estimates.

[#1]

In Standard Least Squares Models > Effect Screening If both Using estimates standardized to have equal variances and Using estimates
orthogonalized to be uncorrelated are selected an Orthog Coded value is listed. According to the manual this column shows the estimate of the parameter resulting from the transformation that is used to orthogonalize the estimates.

What sort of transformation is used? These values differ a lot from the estimates without transformation. 

[#2]

Hi @NaiveElk787 : Welcome! Can you show your output so we can better assess exactly what you are asking?

[#3]

[#4]

Hi @NaiveElk787 . I confess that I am unfamiliar with this JMP output/option. Can you provide a link to the help manual that you mention?

[#5]

Sure, 

https://www.jmp.com/content/dam/jmp/documents/en/support/jmp18/fitting-linear-models.pdf

https://www.jmp.com/support/help/en/18.0/#page/jmp/effect-screening-plot-options.shtml

[#6]

Hi @NaiveElk787 : In the pdf file that you provided a link to, it says "The option Using estimates orthogonalized to be uncorrelated applies a transformation to remove correlation. This option is selected by default when the estimates are correlated. The transformation that is applied is identical to the transformation that is used to calculate sequential sums of squares. The estimates measure the additional contribution of the variable after all previous variables have been entered into the model".

Hmm,  I've never really thought of the calculation of sequential sums of squares  (sometimes called Type 1 SS) as a "transformation".  So perhaps others can comment? In the meantime, I'll point you here:

https://www.math.arizona.edu/~piegorsch/571A/STAT571A.Ch07.pdf