# Create a complete experimental design with graph of design layout and skeletal ANOVA table ```r design( type, treatments, reps, nrows, ncols, brows = NA, bcols = NA, byrow = TRUE, sub_treatments = NULL, fac.names = NULL, fac.sep = c("", " "), buffer = NULL, plot = TRUE, rotation = 0, size = 4, margin = FALSE, save = FALSE, savename = paste0(type, "_design"), plottype = "pdf", seed = TRUE, quiet = FALSE, ... ) ``` ## Arguments - `type`: The type of design. Supported design types are `crd`, `rcbd`, `lsd`, `crossed:` where `` is one of the previous types, and `split`. See Details for more information. - `treatments`: A vector containing the treatment names or labels. - `reps`: The number of replicates. Ignored for Latin Square Designs. - `nrows`: The number of rows in the design. - `ncols`: The number of columns in the design. - `brows`: For RCBD and Split Plot designs. The number of rows in a block. - `bcols`: For RCBD and Split Plot designs. The number of columns in a block. - `byrow`: For split-plot only. Logical (default `TRUE`). Provides a way to arrange plots within whole-plots when there are multiple possible arrangements. - `sub_treatments`: A vector of treatments for sub-plots in a split plot design. - `fac.names`: Allows renaming of the `A` level of factorial designs (i.e. those using `agricolae::design.ab()`) by passing (optionally named) vectors of new labels to be applied to the factors within a list. See examples and details for more information. - `fac.sep`: The separator used by `fac.names`. Used to combine factorial design levels. If a vector of 2 levels is supplied, the first separates factor levels and label, and the second separates the different factors. - `buffer`: A string specifying the buffer plots to include for plotting. Default is `NULL` (no buffers plotted). Other options are "edge" (outer edge of trial area), "rows" (between rows), "columns" (between columns), "double row" (a buffer row each side of a treatment row) or "double column" (a buffer row each side of a treatment column). "blocks" (a buffer around each treatment block) will be implemented in a future release. - `plot`: Logical (default `TRUE`). If `TRUE`, display a plot of the generated design. A plot can always be produced later using `autoplot()`. - `rotation`: Rotate the text output as Treatments within the plot. Allows for easier reading of long treatment labels. Takes positive and negative values being number of degrees of rotation from horizontal. - `size`: Increase or decrease the text size within the plot for treatment labels. Numeric with default value of 4. - `margin`: Logical (default `FALSE`). Expand the plot to the edges of the plotting area i.e. remove white space between plot and axes. - `save`: One of `FALSE` (default)/`"none"`, `TRUE`/`"both"`, `"plot"` or `"workbook"`. Specifies which output to save. - `savename`: A file name for the design to be saved to. Default is the type of the design combined with "_design". - `plottype`: The type of file to save the plot as. Usually one of `"pdf"`, `"png"`, or `"jpg"`. See `ggplot2::ggsave()` for all possible options. - `seed`: Logical (default `TRUE`). If `TRUE`, return the seed used to generate the design. If a numeric value, use that value as the seed for the design. - `quiet`: Logical (default `FALSE`). Hide the output. - `...`: Additional parameters passed to `ggplot2::ggsave()` for saving the plot. ## Returns A list containing a data frame with the complete design (`$design`), a ggplot object with plot layout (`$plot.des`), the seed (`$seed`, if `return.seed = TRUE`), and the `satab` object (`$satab`), allowing repeat output of the `satab` table via `cat(output$satab)`. ## Details The designs currently supported by `type` are Completely Randomised designs (`crd`), Randomised Complete Block designs (`rcbd`), Latin Square Designs (`lsd`), Factorial with crossed structure (use `crossed:` where `` is one of the previous types e.g. `crossed:crd`) and Split Plot designs (`split`). Nested factorial designs are supported through manual setup, see Examples. If `save = TRUE` (or `"both"`), both the plot and the workbook will be saved to the current working directory, with filename given by `savename`. If one of either `"plot"` or `"workbook"` is specified, only that output is saved. If `save = FALSE` (the default, or equivalently `"none"`), nothing will be output. `fac.names` can be supplied to provide more intuitive names for factors and their levels in factorial and split plot designs. They can be specified in a list format, for example `fac.names = list(A_names = c("a", "b", "c"), B_names = c("x", "y","z"))`. This will result a design output with a column named `A_names` with levels `a, b, c` and another named `B_names` with levels `x, y, z`. Labels can also be supplied as a character vector (e.g. `c("A", "B")`) which will result in only the treatment column names being renamed. Only the first two elements of the list will be used, except in the case of a 3-way factorial design. `...` allows extra arguments to be passed to `ggsave()` for output of the plot. The details of possible arguments can be found in `ggplot2::ggsave()`. ## Examples ```r # Completely Randomised Design des.out <- design(type = "crd", treatments = c(1, 5, 10, 20), reps = 5, nrows = 4, ncols = 5, seed = 42) # Randomised Complete Block Design des.out <- design("rcbd", treatments = LETTERS[1:11], reps = 4, nrows = 11, ncols = 4, brows = 11, bcols = 1, seed = 42) # Latin Square Design # Doesn't require reps argument des.out <- design(type = "lsd", c("S1", "S2", "S3", "S4"), nrows = 4, ncols = 4, seed = 42) # Factorial Design (Crossed, Completely Randomised) des.out <- design(type = "crossed:crd", treatments = c(3, 2), reps = 3, nrows = 6, ncols = 3, seed = 42) # Factorial Design (Crossed, Completely Randomised), renaming factors des.out <- design(type = "crossed:crd", treatments = c(3, 2), reps = 3, nrows = 6, ncols = 3, seed = 42, fac.names = list(N = c(50, 100, 150), Water = c("Irrigated", "Rain-fed"))) # Factorial Design (Crossed, Randomised Complete Block Design), # changing separation between factors des.out <- design(type = "crossed:rcbd", treatments = c(3, 2), reps = 3, nrows = 6, ncols = 3, brows = 6, bcols = 1, seed = 42, fac.sep = c(":", "_")) # Factorial Design (Nested, Latin Square) trt <- c("A1", "A2", "A3", "A4", "B1", "B2", "B3") des.out <- design(type = "lsd", treatments = trt, nrows = 7, ncols = 7, seed = 42) # Split plot design des.out <- design(type = "split", treatments = c("A", "B"), sub_treatments = 1:4, reps = 4, nrows = 8, ncols = 4, brows = 4, bcols = 2, seed = 42) # Alternative arrangement of the same design as above des.out <- design(type = "split", treatments = c("A", "B"), sub_treatments = 1:4, reps = 4, nrows = 8, ncols = 4, brows = 4, bcols = 2, byrow = FALSE, seed = 42) ```

design function