One definition of statistical validity:
https://explorable.com/statistical-validity
Statistical validity refers to whether a statistical study is able to draw conclusions that are in agreement with statistical and scientific laws. This means if a conclusion is drawn from a given data set after experimentation, it is said to be scientifically valid if the conclusion drawn from the experiment is scientific and relies on mathematical and statistical laws.
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It is the set of model parameters which minimizes the sum of the squares of the differences between the actual and model-predicted alliance scores. This is universally understood.
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This is the point upon which we disagree. This is not a mathematical exercise--it is a statistical one. And statistical analysis requires inference about the validity of the estimated parameters. And I strongly believe that the many students who will be working in engineering in the future who read this need to understand that this is a statistical exercise which requires all of the caveats of such analysis.
Here's a discussion for fixed effects from the SAS manual:
http://www.sas.com/storefront/aux/en...48_excerpt.pdf