Displayr

Ability to apply a different weight to a specified column.

I attempted to create a template from weight variables, but it didn't work as expected. The weight definitions were not included when inserting the template into another document. It would be helpful if DisplayR could support weight variables in templates, allowing for seamless transfer and application of weight definitions across documents.

Apply a global weight to a document so that you can swap out the weight applied throughout the whole document in one go. The weight should then be applied to all outputs that accept weights. Currently, swapping out weights for testing/checking requires individual selection of multiple objects that allow weights.

Allow users to specify the value to which they want the weight to sum. This can be done by specifying Population Targers and getting the Sum to match Targets. Users can add % targets and specify the value to which they want the SUM the weights. E.g. Input Gender targets and 50%/ 50% and Input Population as Make Weights to SUM menu

There are situations where RIM weighting using multiple adjustment variable sets produces the error that the weighting algorithm can't converge due to sampling issues. What isn't clear without trial and error is what specific cells or combinations of cells are causing this issue. What would be helpful is for the weighting module to produce a summary of which cells are contributing to the weighting error.

In Q there is a time series analysis option which lets you turn on or off Weight periods equally but this can’t be turned off from within Displayr: !image-20231010-232854.png|width=262,height=148!

A way for tables created in explore mode to automatically have a weight applied.

Ability to turn weights on/off for the entire Document in Edit and View mode.

The weighting and Binary Complicated Filters modules in Q should be added to Displayr as functions are clearly missing and the alternative is only R.

When you create a weight in Displayr, it allows you to choose variables from multiple data sets as adjustment variables but the weighting appears to only be correct when you have all the weighting questions in the same data set. A warning message should make this known to the customer.