Create weighted data grids

[strengejacke]

1. @strengejacke Do you think we could implement a way in modelbased to automatize the weighted approach? I.e., compute a weighted datagrid upfront

Originally posted by @DominiqueMakowski in #639

[DominiqueMakowski]

Idea:

1. Create a "fast" mode
2. First, stresstest by making it available only if all predictors are categorical (in the future, we could imagine binning continuous variables to approximate results, it could still be useful for massive datasets)
3. This fast mode creates a weighted datagrid (perhaps "weighted" is a feature to be added to get_datagrid, which would add a weight column)
4. These weights are then used by marginaleffects
5. Question: I reckon this only applies to some type of marginalization approaches

[strengejacke]

• For estimate = "specific" (similar to estimate_relation()) and ``estimate = "typical"(default),by` creates a data grid that is passed to `newdata` (i.e., filtering works "by design").
• For estimate = "average", by is used for the by argument in marginaleffects, where the full data is used. Possible filtering in by requires that the "filter values/levels" are present in the data. newdata is not used.
• For estimate = "population", by is used to create a data grid, and the unique values for each variable in that data grid are passed to the variables argument in marginaleffects (i.e., filtering works "by design"). newdata is not used.

However: you can always specify newdata (or our alias data). If explicitly set, it will then be used as newdata way for all estimate options, meaning that the "fast" option should always work (unless marginaleffects handles newdata differently than expected).

[strengejacke]

Do we want to explicitly have an option/argument to internally trigger a weighted data grid, or is it sufficient to have it in insight::get_datagrid() only? Although we can simply pass the weighted argument to insight::get_datagrid() and document it in modelbased.

[DominiqueMakowski]

Do we want to explicitly have an option/argument to internally trigger a weighted data grid

You mean from like estimate_means/contrasts/slopes? Perhaps a fast argument could be quite explicit - especially if we verify that it indeed leads to speedups. Alternatively, exposing a weighted argument should work too, and we can document it by saying that it can be used for potential memory/efficiency benefits