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(Available only for continuous X variables.) Enables you to predict an X value, given specific values for Y and the other X variables. For more information about the Inverse Prediction option, see Inverse Prediction in Standard Least Squares Report and Options.
Σ = -H-1
where H is the Hessian (or second derivative) matrix evaluated using the parameter estimates on the last iteration. Note that the dispersion parameter, whether estimated or specified, is incorporated into H. Rows and columns corresponding to aliased parameters are not included in Σ.
Shows or hides a correlation matrix for all the effects in a model. The correlation matrix is the normalized covariance matrix. For each σij element of Σ, the corresponding element of the correlation matrix is σij/σiσj, where .
Note: You can change the α level for the confidence limits in the Fit Model window by selecting Set Alpha Level from the red triangle menu.
Note: You can change the α level for the confidence limits in the Fit Model window by selecting Set Alpha Level from the red triangle menu.
See Redo Menus and Save Script Menus in the Using JMP book for more information about the following options:

Help created on 3/19/2020