seq_lewis: Lewis _et al._ (1988) cross-over design specification
In mjg211/xover: Design and analysis of cross-over clinical trials

Description Usage Arguments Details Value Author(s) References Examples

Specifies cross-over designs from Lewis et al. (1988).

1 2	seq_lewis(D = 4, selection = 1, labels = 0:(D - 1), as_matrix = T, summary = T)

`D`	The number of treatments. Must be either four, six, eight, or nine. Defaults to `4`.
`selection`	A single `numeric` integer indicating which design to return, for the chosen value of `D`. See Details for information on supported values.
`labels`	A `vector` of labels for the treatments. Should be of `length` `D`, containing unique elements. Defaults to `0:(D - 1)`.
`as_matrix`	A `logical` variable indicating whether the design should be returned as a `matrix`, or a `tibble`. Defaults to `T`.
`summary`	A `logical` variable indicating whether a summary of the function's progress should be printed to the console. Defaults to `T`.

seq_lewis() supports the specification of designs from Lewis et al. (1988). Designs for four, six, eight, and nine treatments (see D) are supported, for any chosen treatment labels (see labels). In addition, the designs can be returned in matrix or tibble form (see as_matrix).

Precisely, for D equal to four, six, eight and nine, there are six, eight, four, and two sets of sequences available respectively (accessible by setting selection equal to one through eight as appropriate). Ultimately, the (k,j)th element of the cross-over design matrix corresponds to the treatment a subject on the kth sequence would receive in the jth period.

Either a matrix if as_matrix = T (with rows corresponding to sequences and columns to periods), or a tibble if as_matrix = F (with rows corresponding to a particular period on a particular sequence). In either case, the returned object will have class xover_seq.

Based on data from the Crossover package by Kornelius Rohmeyer.

Lewis SM, Fletcher DJ, Matthews JNS (1988) Factorial cross-over designs in clinical trials. In Optimal Design and Analysis of Experiments, Eds: Dodge Y, Fedorov VV, Wynn HP, pp 133-140. Elsevier Science Publishers BV: North-Holland.

# Lewis et al. (1988) designs for nine treatments
lewis1         <- seq_lewis(D = 9)
lewis2         <- seq_lewis(D = 9, selection = 2)
# Using different labels
lewis1_LETTERS <- seq_lewis(D = 9, labels = LETTERS[1:9])
lewis2_LETTERS <- seq_lewis(D = 9, selection = 2, labels = LETTERS[1:9])
# Returning in tibble form
lewis1_tibble  <- seq_lewis(D = 9, as_matrix = F)
lewis2_tibble  <- seq_lewis(D = 9, selection = 2, as_matrix = F)