Use this to predict the value for a future observation based on the current fitted hierarchical generalized linear model.
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.|
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.
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.
Enter the weights when the Specify option is selected for the standardization method.
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.
Specify a values of offset on which to base the predictions.
Lists the type of back-transformations that you can apply to the values on the linear scale, before calculating the predicted means.
Specifies which items of output are to be produced.
|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|
|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.