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Enables easy distribution of samples per batch avoiding batch and confounding effects by randomization of the variables in each batch.

Details

The most important function is design(), which distributes samples in batches according to the information provided.

To help in the bench there is the inspect() function that appends the group to the data provided.

If you have a grid or some spatial data, you might want to look at the spatial() function to distribute the samples while keeping the original design.

In case an experiment was half processed and you need to extend it you can use follow_up() or follow_up2(). It helps selecting which samples already used should be used in the follow up.

Author

Lluís Revilla