seq_pigeon: Pigeon (1984) 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 Pigeon (1984).

1 2	seq_pigeon(D = 3, selection = 1, labels = 0:(D - 1), as_matrix = T, summary = T)

`D`	The number of treatments. Must be a single `numeric` integer between three and seven inclusive. Defaults to `3`.
`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_pigeon() supports the specification of designs from Pigeon (1984). Designs for three through seven 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 three through seven, there are one, four, six, seven, and two designs available respectively (accessible by setting selection equal to one through seven as appropriate). Ultimately, the (k,j)th element of the cross-over design matrix corresponds to the treatment a subject on the ifelsehtmlkkth 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.

Pigeon JG (1985) Residual effects designs for comparing treatments with a control. PhD thesis, Temple University.

# Pigeon (1984) designs for four treatments
pigeon1        <- seq_pigeon(D = 4)
pigeon2        <- seq_pigeon(D = 4, selection = 2)
pigeon3        <- seq_pigeon(D = 4, selection = 3)
pigeon4        <- seq_pigeon(D = 4, selection = 4)
# Using different labels
pigeon1_ABCD   <- seq_pigeon(D = 4, labels = LETTERS[1:4])
pigeon2_ABCD   <- seq_pigeon(D = 4, selection = 2, labels = LETTERS[1:4])
pigeon3_ABCD   <- seq_pigeon(D = 4, selection = 3, labels = LETTERS[1:4])
pigeon4_ABCD   <- seq_pigeon(D = 4, selection = 4, labels = LETTERS[1:4])
# Returning in tibble form
pigeon1_tibble <- seq_pigeon(D = 4, as_matrix = F)
pigeon2_tibble <- seq_pigeon(D = 4, selection = 2, as_matrix = F)
pigeon3_tibble <- seq_pigeon(D = 4, selection = 3, as_matrix = F)
pigeon4_tibble <- seq_pigeon(D = 4, selection = 4, as_matrix = F)