[Ifeffit] R-factor and reduced chi square

[Scott Calvin]

At 01:07 PM 10/4/2005 -0500, you wrote:
>Hi,
>   I understand R-factor and reduced chi square are statistical ways to
>see if the model is reasonable (R-factor) and if one model is better
>than the others (reduced chi square). But how much should I read into it?
>
>    I have model A and B, I believe A is more theoretical sound than B.
>but when I fit them using IFEFFIT, the R-factor and reduced chi square
>of B is slightly better than A (B: 0.03, 28; A: 0.04, 33). What does
>that tell me? Is my assumption incorrect? Or are they more or less the same?
>

There are some entries related to this topic on the ifeffit FAQ:

http://cars9.uchicago.edu/cgi-bin/ifeffit/faqwiz?req=index

But to answer your question directly, I wouldn't read too much into
r-factors and reduced chi-squares that are that close. All you know is that
both models fit the data reasonably well, but not extremely well. In other
words, statistical quality of fit is not distinguishing the models.

You should look, however, at the fitted parameters. It may be that fit B,
for example, is giving some physically unreasonable parameters (negative
sigma2's, or absurd bond lengths, or E0's that are off of the rising
portion of the edge, or...) while fit A is not. In that case, fit A is
certainly to be preferred.

Or it may be that you have external evidence (including theoretical
predictions) that model A is preferable. In that case, you can't use EXAFS
to SUPPORT the choice of model A, but you can use it to confirm that model
A is a POSSIBLE solution, and to extract additional information (i.e. the
guessed parameters) on the assumption that it is correct.

--Scott Calvin
Sarah Lawrence College