Predictions from Hierarchical Generalized Linear Model

Use this to predict the value for a future observation based on the current fitted hierarchical generalized linear model.

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 a name to copy it into the appropriate list. You can transfer multiple selections from Available data by holding the Ctrl key on your keyboard while selecting items, then click to move them all across in one action.

List of explanatory variates

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 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 the Change values button.

New variate	Opens a window that lets you specify the name of an explanatory variate and the value to predict the response variable from.
Change values	Opens a window that lets you change the values of the currently selected explanatory variables.
Remove	Deletes the selected explanatory variates from the list.

Grouping factors

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 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 the Change values button.

New factor	Opens a window that lets you 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	Opens a window that lets you change the values of the currently selected grouping factors.
Remove	Deletes the selected grouping factors from the list.

Note, if both the Grouping factors and Explanatory variates are left empty, the terms in the fixed model of the HGLM will be predicted.

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 lets you explicitly specify the weightings to be used in the predictions by entering the weights in the space provided.

Weights

Enter the weights when the Specify option is selected for the standardization method.

Combinations

Lets you 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

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.

Predictions	Predictions
Description	Describes the standardization policies used when forming predictions
Standard errors	Standard errors of predictions
Standard error of differences	Standard error of differences between predictions

Save

Predictions	Table or scalar	Predicted values for each response value
Standard errors	Table or scalar	Standard errors for each predicted value

Display in spreadsheet

Display the saved results in a new spreadsheet window.

Plot table of predictions

If this is selected, the predictions will be plotted. The Options button opens the Plot table of predictions dialog which controls how the predictions are plotted. You need to complete either the Grouping factors or Explanatory variates before using the Options button.