Predictions from Hierarchical Generalized Linear Model

This menu allows you to predict the value for a future observation based on the current fitted hierarchical generalized linear model.

List of Explanatory Variates

Provides a space for you to enter the names of the variates that you want to use in the prediction. You can add a new variate name to the list by either double-clicking the name in the Available Data list or by clicking on the New Variate button. You can change the values to predict the response variable from by either double-clicking on an explanatory variable name or by selecting the names and clicking on the Change Values button.

New Variate

Generates a menu that allows you to specify the name of an explanatory variate and the value to predict the response variable from.

Change Values

Generates a menu that allows you to change the values of the currently selected explanatory variables.

Remove

Deletes the selected explanatory variates from the list.

Grouping Factors

Provides a space for you to enter the names of the factors that you want to use in the prediction. You can add a new factor name to the list by either double-clicking the name in the Available Data list or by clicking on the New Factor button. You can change the levels to predict the response variable from by either double-clicking on a name or by selecting the names and clicking on the Change Values button.

New Factor

Generates a menu that allows you to specify the name of a Grouping Factor and the grouping levels at which the predictions for the response variable are to be calculated.

Change Values

Generates a menu that allows you to change the values of the currently selected grouping factors.

Remove

Deletes the selected grouping factors from the list.

Available Data

Lists variates and factors that can be used to supply the explanatory variates and/or grouping factors to be used in the prediction. Double-click on a name to copy it into the appropriate list. Multiple selections can be copied into the lists by selecting the names and clicking on the button.

Standardization Method

Allows you standardize the table of predictions. The Marginal option standardizes the table of predictions by weighting by the number of observations within each level of the factor(s). Equal standardizes by having equal weight for each of the levels of the factor(s). The Specify option allows you to explicitly specify the weightings to be used in the predictions by entering the weights in the space provided.

Weights

Provides a space for you to enter the weights when the Specify option is selected for the standardization method.

Combinations

Allows you to specify how the factors in the current model can be included in the prediction. Select the type of combination that you want to use in the prediction.

Offset

Provides a space for you to specify a values of offset on which to base the predictions.

Back Transform

Lists the type of back-transformations that you can apply to the values on the linear scale, before calculating the predicted means.

Display

Specifies which items of output are to be produced.
Predictionspredictions
Descriptiondescribes the standardization policies used when forming predictions
Standard Errorsstandard errors of predictions
Standard Error of differencesstandard error of differences between predictions
LSDsleast significant differences between predictions. The LSD significance level (%) can be specified in the space provided.

Save

Predictionstable or scalarPredicted values for each response value
Standard Errorstable or scalarStandard Errors for each predicted value

Display In Spreadsheet

Display the saved results in a new spreadsheet window.

See Also