Re: OT compare & contrast Linear Mixed Models :: Complex Samples

Posted by Ryan on Feb 22, 2017; 4:31pm
URL: http://spssx-discussion.165.s1.nabble.com/OT-compare-contrast-Linear-Mixed-Models-Complex-Samples-tp5733875p5733883.html

Art,

There are theoretical differences and differences in the algorithms which could lead to different results. 

Please read this SUGI paper. The last example is particularly relevant. 

http://www2.sas.com/proceedings/sugi31/193-31.pdf

Ryan 

Sent from my iPhone

On Feb 22, 2017, at 9:32 AM, Art Kendall <[hidden email]> wrote:

Since the mid 90's I have have had an entry on my TO DO List, that says that
"there are many logical similarities between Linear Mixed Models and Complex
Samples".

I retired in 2001 and have decided that I'll never have a chance to work
this out.

Over the years there have been many instances where different dialects of
statistics have been found to be very much the same thing ANOVA and
Regression (Cohen); Clustering, Pattern Detection, Unsupervised Learning;
Discriminant function analysis, Pattern Recognition, Supervised Learning.

When I mention the similarity of Mixed models and Complex samples to a top
math psychologist/statistician, he said "of course thy are similar." A top
sampling expert said that they are often identical but sometimes differ. We
did not have time to get into when they would differ.

It would make a good publication to
(1) compare/contrast the logic
(2) compare/contrast the math
(3) run some actual or textbook analyses both ways and compare/contrast the
details and conclusions.

Or has anybody already worked this out?



-----
Art Kendall
Social Research Consultants
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