Vincent Granville asked 16 March 2012 00:40: "should general linear models (for statistical inference) still be taught? Shouldn't the curriculum focus on sophisticated computer-intensive simulations ... The advantages are: ... model-free, non parametric approach, applies to any type of data"
My bugbear is the confusion created by the phrase "general linear model", promoted by eg SAS, which is a limited subset of "generalized linear models". The latter *should* be taught. The suggestion that simulations are model-free and non-parametric (ie distribution free) is irrational. How can you run a simulation without a model based on distributions?
Allan
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