Dear All,

 

Would it be recommended to compare reduced chi square (RCS) values from the fit of the second shell only?  While fitting the second shell only, the differences between RCS values of different models can be greater than when including both the first and second shells in the fit.  For example, the RCS values of model 1 and model 2 for fits of the first and second shells versus just the second shell are 45 and 18, and then 60 and 17, respectively. This to me indicates that fitting the second shell separately from the first gave me a slightly better description of the misfit in that R-range.  Regardless of the fitting range the RCS values say model 2 improves the fit significantly.

 

However, if I use an F-test to compare models while fitting the second shell only, I’ve found that the difference between the models is actually less important than when including both the first and second shells in the fit. For examples, the F-test values of model 1 versus model 2 for fits of the first and second shell versus just the second shell are P=0.047 and then P=0.113, respectively.  This is perhaps caused by the small R-range and hence decreased Nind when fitting the second shell only.

 

However, it also indicates to me that the F-test says perhaps one fitting model is not such an improvement on the fit as I thought it was based purely on the decrease in RCS value.  I assume significant decreases in RCS values to be about >2x, and P <0.05 for the F-test.

 

Should RCS values and F-tests for comparing fitting models only be used when fitting two shells together or can they be used when just fitting the second shell?

 

Kind regards,

Matt Siebecker