> > jim clark wrote: > > While I agree, I would remove the "especially". Contrasts, especially > > the polynomial contrasts that SPSS prints out are not going to be useful > > in most cases unless the contrasts map onto clear (a priori) theoretical > > predictions. For example, it is pretty rare that a quartic or cubic > > contrast is readily interpretable in most contexts that I'm familiar with. > > I think Thom and I pretty much agree, although our wording and > emphasis might differ. But sometimes contrasts can be useful
Agreed. > even when the "theory" is weak. If one has ordered levels of a > factor (and little else to go on), for example, it is true that Yes - I'd argue this kind of a priori order (e.g., age related progression in children) does have theory attached (though not necessarily formal theory). We're just quibbling about semantics. > the cubic or quartic or other higher-order components might > rarely be useful. Nonetheless, a substantial loading of SS > treatment on the single df linear component can enhance the Yes - the linear component is probably the most useful IF the levels of the factor are ordered and k>2. Even then the linear component significance is often often over-interpreted (e.g., with three levels most increases or decreases will be significant regardless of whether the underlying increase in linear or not). Thom . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
