Random Effect Block (generalized linear mixed models)
Enter effects into the model by selecting one or more fields in the source list and dragging to the effects list. The type of effect created depends upon which hotspot you drop the selection. Categorical (nominal, and ordinal) fields are used as factors in the model and continuous fields are used as covariates.
- Main. Dropped fields appear as separate main effects at the bottom of the effects list.
- 2-way. All possible pairs of the dropped fields appear as 2-way interactions at the bottom of the effects list.
- 3-way. All possible triplets of the dropped fields appear as 3-way interactions at the bottom of the effects list.
- *. The combination of all dropped fields appear as a single interaction at the bottom of the effects list.
Buttons to the right of the Effect Builder allow you to perform various actions.
| Icon | Description |
|---|---|
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Delete terms from the model by selecting the terms you want to delete and clicking the delete button. |
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Reorder the terms within the model by selecting the terms you want to reorder and clicking the up or down arrow. |
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Add nested terms to the model using the Add a Custom Term (generalized linear mixed models) dialog, by clicking on the Add a Custom Term button. |
Include Intercept. The intercept is not included in the random effects model by default. If you can assume the data pass through the origin, you can exclude the intercept.
Define covariance groups by. The categorical fields specified here define independent sets of random effects covariance parameters; one for each category defined by the cross-classification of the grouping fields. A different set of grouping fields can be specified for each random effect block. All subjects have the same covariance type; subjects within the same covariance grouping will have the same values for the parameters.
Subject combination. This allows you to specify random effect subjects from preset combinations of subjects from the Data Structure tab. For example, if School, Class, and Student are defined as subjects on the Data Structure tab, and in that order, then the Subject combination dropdown list will have None, School, School * Class, and School * Class * Student as options.
Random effect covariance type. This specifies the covariance structure for the residuals. The available structures are:
- First-order autoregressive (AR1)
- Autoregressive moving average (1,1) (ARMA11)
- Compound symmetry
- Diagonal
- Scaled identity
- Toeplitz
- Unstructured
- Variance components