Missing Values | JMP 13.2

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Fitting Linear Models • Standard Least Squares Report and Options • Launch the Standard Least Squares Personality • Missing Values

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By default, rows that have missing values for Y or any model effects are excluded from the analysis.

Note: JMP provides an Informative Missing option in the Fit Model window in the Model Specification red triangle menu. Informative Missing enables you to fit models using rows where model effects are missing. See Informative Missing in Model Specification for details.

When your model contains a random effect, Y values are fit separately by default. The individual reports appear in the Fit Group report.

Suppose that your model contains only fixed effects, and the following statements are true:

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You specified more than one Y response.

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Some of these Y responses have missing values.

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You did not select the Fit Separately option in the Fit Model launch window.

Then, JMP prompts you to select one of the following options:

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Fit Separately fits each Y using all rows that are nonmissing for that particular Y.

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Fit Together fits each Y uses only those rows that are nonmissing for all of the Y variables.

When you select Fit Separately, a Fit Group report contains the individual reports for the Y variables. You can select profilers from the Fit Group red triangle menu to view all the Y variables in the same profiler. Alternatively, you can select a profiler from an individual Y variable report to view only that variable in the profiler.

When you select Fit Together, a Fit Least Squares report contains individual reports for each of the Y variables. However, some parts of the report are combined for all Y variables: the Effect Summary and the Profilers.

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Help created on 9/19/2017