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Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user

I would like to compare the goodness of fit for a regression model fitted to two separate groups (patients and controls).

I want to compare goodness of fit (as opposed to difference in slope). I thought one way of doing this would be comparing the R value of the model in patients vs the value in controls in a Fisher R-to-z comparison.

My question is whether it is more appropriate to use the 'Multiple R-squared' or the 'Adjusted R-squared'. Additionally if the Adjusted R squared is preferred then how would one deal with negative values?

Or please do let me know if the whole approach is wrong headed

Thanks

Rob.

I would like to compare the goodness of fit for a regression model fitted to two separate groups (patients and controls).

I want to compare goodness of fit (as opposed to difference in slope). I thought one way of doing this would be comparing the R value of the model in patients vs the value in controls in a Fisher R-to-z comparison.

My question is whether it is more appropriate to use the 'Multiple R-squared' or the 'Adjusted R-squared'. Additionally if the Adjusted R squared is preferred then how would one deal with negative values?

Or please do let me know if the whole approach is wrong headed

Thanks

Rob

I would like to compare the goodness of fit for a regression model fitted to two separate groups (patients and controls).

I want to compare goodness of fit (as opposed to difference in slope). I thought one way of doing this would be comparing the R value of the model in patients vs the value in controls in a Fisher R-to-z comparison.

My question is whether it is more appropriate to use the 'Multiple R-squared' or the 'Adjusted R-squared'. Additionally if the Adjusted R squared is preferred then how would one deal with negative values?

Or please do let me know if the whole approach is wrong headed.

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Bumped by Community user
Bumped by Community user
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RobMcC
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Comparing goodness of fit in linear regression

I would like to compare the goodness of fit for a regression model fitted to two separate groups (patients and controls).

I want to compare goodness of fit (as opposed to difference in slope). I thought one way of doing this would be comparing the R value of the model in patients vs the value in controls in a Fisher R-to-z comparison.

My question is whether it is more appropriate to use the 'Multiple R-squared' or the 'Adjusted R-squared'. Additionally if the Adjusted R squared is preferred then how would one deal with negative values?

Or please do let me know if the whole approach is wrong headed

Thanks

Rob