Posted by
James Algina on
Feb 22, 2017; 7:41pm
URL: http://spssx-discussion.165.s1.nabble.com/OT-compare-contrast-Linear-Mixed-Models-Complex-Samples-tp5733875p5733885.html
Hi Art,
This reference may be of some interest
Sterba, S. K. (2009) Alternative Model-Based and Design-Based Frameworks for Inference From Samples to Populations:
From Polarization to Integration. MBR. 44:6, 711-740. DOI:10.1080/00273170903333574
Jamie
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of Art Kendall
Sent: Wednesday, February 22, 2017 9:32 AM
To:
[hidden email]
Subject: OT compare & contrast Linear Mixed Models :: Complex Samples
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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