blockEfficiencies

<p>a model formula for the required treatments design where the default 
formula assumes a fully crossed factorial treatment model.</p>

treatments_model

<p>Finds D-efficiency for general treatment and block designs.</p>

Constructs D-optimal or near D-optimal nested and crossed
block designs for unstructured or general factorial treatment designs.
The treatment design, if required, is found from a model
matrix design formula and can be added sequentially, if required.
The block design is found from a defined
set of block factors and is conditional on the defined treatment design.
The block factors are added in sequence and each added block factor
is optimized conditional on all previously added block factors.
The block design can have repeated nesting down to any required
depth of nesting with either simple nested blocks or a
crossed blocks design at each level of nesting. Outputs include a table
showing the allocation of treatments to blocks and tables showing
the achieved D-efficiency factors for each block and treatment design.

Rodney Edmondson

State of Data and AI Literacy Report 2025

blockEfficiencies: D-Efficiency factors

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