On Dec 7, 12:13 pm, djh <halitsk...@att.net> wrote: > It didn't occure to me to ask if we must say S,N (instead of N,S) if > we've said "Subset x MoSS" (not MoSS x Subset). > > If we're obligated to do so, then of course the two tables must be > presented as: > > SE and p values for u^2 in regression c on (e,u,u*e,u^2) for each > value of subset x MoSS | (Fold,Set,Len) = (all,all,all) > -------------------- > Subset > x u^2 > MoSS SE p > > S,N 35.17 0.457 > C,N 38.19 0.416 > S,R 36.88 0.434 > C,R 34.69 0.438 > -------------------- > > SE and p values for u*e in the regression c on (u,e,u*e), for each > value of subset x MoSS | (Fold,Set,Len) = (all,all,all) > -------------------- > Subset > x u*e > MoSS SE p > > S,N 0.491 0.454 > C,N 0.602 0.462 > S,R 0.547 0.463 > C,R 0.512 0.478
1. What does "(Fold,Set,Len) = (all,all,all)" mean?
2. Something's wrong somewhere. Those p's are too similar to one another, and are too large to be consistent with the other results you've been reporting.
3. If all the p's for u^2 are truly that big then you should probably drop the quadratic model. Model selection generally starts with the most complicated model and works down. In particular, you should not be considering any results from regressing c on (u,u^2) if e matters.
4. SEP = sqrt[Residual Sum of Squares / df] = sqrt[Residual Mean Square] Are you sure Ivo's program doesn't give that as optional output?
5. Let the constant in the input to Ivo's program default to 1.
6. I have a hunch that Het may be related to a Subset x Fold interaction, where the d.v. is the average slope.
7. Your forthcoming explanation "using reasoning based on the behavior of the average slope Auq of c on (u,u^2) and the covariance AubC of e and u in c on (u,e,u*e)" will probably go right over my head, because I have only a hunch about what the average slope Auq of c on (u,u^2) might mean, and not a clue about what the covariance AubC of e and u in c on (u,e,u*e) might mean.