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Visual Statistics Procedures
 

SANDWICH Procedure

Fit Statistics

The "Fit Statistics" table displays fit statistics for the model. These statistics include the following:

  • Root MSE, an estimate of the standard deviation of the error term. It is calculated as the square root of the mean square error.

  • R-square, a measure between 0 and 1 that indicates the portion of the (corrected) total variation that is attributed to the fit rather than left to residual error. It is calculated as SS(Model) divided by SS(Total) and is also called the coefficient of determination. It is the square of the multiple correlation—in other words, the square of the correlation between the dependent variable and the predicted values.

  • Adj R-Sq, the adjusted R-square, which is a version of R-square that has been adjusted for the number of parameters in the model. It is calculated as

    upper R overbar squared equals 1 minus StartFraction left-parenthesis n minus i right-parenthesis left-parenthesis 1 minus upper R squared right-parenthesis Over n minus p EndFraction

    where i is equal to 1 if there is an intercept and 0 otherwise, n is the number of observations that are used to fit the model, and p is the number of parameters in the model.

Last updated: June 22, 2026