This is very interesting-- thanks for the reply Nick. I didn't know
that this was more or less uniquely a Stata application, that does
limit the ability to conveniently use it outside of the Stata
community. Has the approach been published anywhere in a peer reviewed
type journal?
On 2/3/06, Nick Cox <[email protected]> wrote:
> On the contrary, this is strongly Stata-related.
>
> It depends what you claimed in your paper, but on this
> report the reviewer and you are at cross-purposes.
>
> Stata's -mspline- chops a scatter plot into vertical bands,
> calculates bivariate medians for each and then interpolates
> the median points using cubic splines. It is not any variety
> of cubic spline smoothing as usually discussed in any literature
> I have sampled. It is
> an idiosyncratic, but often quite useful, exploratory or heuristic
> smoothing technique. Personally I wouldn't include it in anything
> I tried to publish outside the Stata community, as to explain
> it properly would entail spelling all this out. (And a reviewer
> might reasonably ask Why this way?)
>
> I don't think the issue of assumptions
> really arises. The main criterion worth discussing is to think
> about the graphical patterns produced and whether you can relate them to
> what you think is going in scientific or practical terms.
> I don't think that even in formal mood or mode anyone should want
> to formalise this in a terms of a model or data generating process.
>
> The reviewer seems to want something much more formal. Also,
> the reviewer may not be understanding quite what the method
> does. His or her specific assertions seem incorrect or irrelevant
> to me, but there are checks that transcend verbal debate. Your results
> should be robust over a variety of choices of numbers of bands and also
> match what other smoothers suggest.
>
> Nick
> [email protected]
>
> Tim Wade
>
> > A statistics question, not really Stata related:
> >
> > In a recent paper, I used median cubic splines to graphically explore
> > non-linearity in the relationship between two continuous variables.
> > The independent variable, although continuous, was slightly clustered
> > and as a result there were some gaps where no data were available. The
> > reviewer said that because of this, the median cubic spline is not
> > appropriate beacuse it is adapted from time series approaches and
> > requires equidistant data of equal weight for meaningful
> > interpretation. I did not find this prerequisite for this approach in
> > any of my references, or in the Stata documentation. Has anyone else
> > encountered this issue? Is the median cubic spline transformation only
> > appropriate when responses are equidistant?
>
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