I'd like to understand better how ordered and non-ordered factors are
treated differently when included as explanatory variables in statistical
models. Also, it appears as though glm [family=binomial] (base) treats
ordered factors differently than lrm (design). For example, when fitting
the same model with each function the inclusion of an ordered factor results
in considerably different coefficients. If I do not specify the factor as
ordered my resulting coefficients (glm and lrm) are essentially identical.
Any personal insight or good references would be much appreciated.
Thanks.
Marc
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