At the start of a data analysis project it is often suggested that the researcher look first at multiple simple models. That is, always begin with simple, one variable at a time analyses, such as multiple single-variable tests for association or significance.
Then, later, somehow (how?) pull all the separate pieces together into a single comprehensive framework, an inclusive data narrative. For detecting true compound effects with more than just marginal associations, this is easily defeated with simple examples.
But more critically, it is looking through the data telescope from wrong end.
Author: James D MalleyJason H Moore
Credits/Source: BioData Mining 2014, 7:13
Published on: 2014-07-18
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News Provider: 7thSpace Interactive / EUPB Press Office
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