Parameter Estimates for Original Predictors | JMP 13.2

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Fitting Linear Models • Generalized Regression Models • Model Fit Reports • Parameter Estimates for Original Predictors

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Parameter Estimates for Original Predictors

The Parameter Estimates for Original Predictors report gives estimates and other results for all parameters in the model. These include the coefficients for predictors and additional parameters such as scale, dispersion, or zero inflation parameters. See Distribution.

Tip: You can select terms in the Parameter Estimates for Original Predictors report to highlight the corresponding paths in the Solution Path Plot. The corresponding columns in the data table are also selected. This is useful when running further analyses. Press Shift and click the terms to select multiple rows.

The Parameter Estimates for Original Predictors report gives parameter estimates for the model expressed in terms of the original (uncentered and unscaled) predictors.

The report provides the following information:

A list of the model terms. “Forced in” appears next to any terms that were forced into the model using the Advanced Controls option.

The parameter estimate corresponding to the model term given in terms of the original measurements.

The standard error of the estimate. This is obtained using M-estimation and a sandwich formula (Zou, 2006, and Huber and Ronchetti, 2009).

The ChiSquare value for a Wald test of whether the parameter is zero.

Prob > ChiSquare

The p-value for the Wald test.

The lower bound for a 95% confidence interval for the parameter. You can change the α level in the Fit Model window by selecting Set Alpha Level from the red triangle menu.

The upper bound for a 95% confidence interval for the parameter. You can change the α level in the Fit Model window by selecting Set Alpha Level from the red triangle menu.

Singularity Details

(Available only if there are linear dependencies among the model terms.) The linear function that the model term satisfies.

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Help created on 9/19/2017