Avoid partial replicate designs, pleeeze! [🇷 for BE/BA]

posted by Helmut Homepage – Vienna, Austria, 2020-07-11 13:57 (1357 d 01:49 ago) – Posting: # 21672
Views: 17,738

Hi ElMaestro,

❝ ❝ Wow! Nobody mastered that in R so far. I don’t want to dampen your enthusiasm but I think that is not possible at all.


❝ Challenge accepted :-)


Good luck! I added the variance-covariance matrices and the complete warnings above.

From this SASians’ document:Further down about

NOTE: Convergence criteria met but final hessian is not positive definite.
The reasons for why this note occurs can vary. The most common reasons for this note relates to scaling issues or misspecified or overspecified models.
A nonpositive definite Hessian matrix can indicate a surface saddlepoint […]. If the MIXED procedure has converged to a saddlepoint, then the final solution given by PROC MIXED is not the optimal solution. To get around this problem, run the model again using different starting values. Try adding a PARMS statement to your PROC MIXED code. Either use the OLS option to specify ordinary least squares starting values (versus the default MIVQUE0 values), or specify your own starting values in the PARMS statement. The syntax for the PARMS statement with the OLS option is simple, as shown below:
   parms / ols;


In my understanding:

You can’t fix by analysis
what you bungled by design.
   Richard J. Light, Judith D. Singer, John B. Willett

100% of all disasters are failures of design, not analysis.   Ronald G. Marks

To propose that poor design
can be corrected by subtle analysis techniques
is contrary to good scientific thinking.
   Stuart J. Pocock

[…] an inappropriate study design is incapable of answering
a research question, no matter how careful the subsequent
methodology, conduct, analysis, and interpretation:
Flawless execution of a flawed design achieves nothing worthwhile.
   J. Rick Turner


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