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

depth of nesting with either simple nested blocks or
crossed blocks at each level of nesting. Outputs include a table

Title: Nested and Crossed Block Designs for Factorial and Unstructured
Description: Constructs D-optimal or near D-optimal treatment and block designs for linear
treatment models with crossed or nested block factors. The treatment design can be any
arbitrary linear model defined by a treatment model formula and the block design can be
any feasible combination of crossed or nested block factors. The block design factors
are optimized sequentially and the levels of each successive block factor are optimized
within the levels of each preceding block factor. Crossed block designs with non-singular
interaction effects are optimized using a weighting scheme that allows for differential
weighting of first and second-order block effects. Outputs include a table showing the
allocation of treatments to blocks and tables showing the achieved D-efficiency factors

Description: Constructs treatment and block designs for linear
feasible linear model and the block design can be any feasible combination of crossed or
nested block factors. The block design is a sum of one or more block factors
and the block design is optimized sequentially with the levels of each successive block factor optimized
conditional on all previously optimized block factors.
D-optimality is used throughout except for square or rectangular lattice block designs
which are constructed algebraically using mutually orthogonal Latin squares.
Crossed block designs with interaction effects are optimized using a weighting scheme
which allows for differential weighting of first and second-order block effects.
Outputs include a table showing the allocation of treatments to blocks and tables showing
Edmondson, R.N. Multi-level Block Designs for Comparative Experiments. JABES (2020).