why my question is marked as spam?? This is a serious question
Link to post:
(SLS REML gives constant intercept offset vs Python/R in highly sparse mixed model)
by xmq
https://community.jmp.com/t5/Discussions/SLS-REML-gives-constant-intercept-offset-vs-Python-R-in-highly/m-p/946188#M109689
I'm fitting a mixed model using Standard Least Squares (REML): Y ~ A(Sum) + B(Sum) + C(Sum) + D(Sum) + Subject(&Random) ~14,000 obs, ~200 levels of factor A, ~60 levels of C, ~120 subjects Highly sparse A×C design: ~97% cells empty (most A-levels appear in only 1 C-level) When I replicate in Python (statsmodels MixedLM, REML), all 200 LS Means for factor A differ from JMP by an exactly constant offset (0.22). Relative effects and rankings are 100% identical (std of pairwise diff = 0.0004). Other findings: For a different response variable on the same data with the same model structure (same X matrix), the offset is only 0.006. The problematic response has higher ICC (0.36 vs 0.27). Questions: Does JMP SLS compute the intercept (or LS Means) differently from a standard V⁻¹-weighted GLS when ICC is moderate-to-high in a sparse design? Is there a known algorithmic difference between SLS (REML) and the Mixed Model personality for this scenario? JMP Pro 17, Windows.
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