Constructs a row-column design using CycDesigN (R.W. Payne).
|Controls printed output (
||Numbers of levels of the treatment factors; if unset, takes the numbers of levels declared for the factors in the
||Number of replicates|
||Number of rows|
||Number of columns|
||Group sizes for a two-factor nested treatment structure|
||Up to four factors to use in the treatment model: one factor for a one-way treatment model, two factors for a nested structure when
||Whether the design is resolvable (
||How to construct the design (
||Number of contiguous rows to latinize; default 0 i.e. not latinized|
||Number of contiguous columns to latinize; default 0 i.e. not latinized|
||Specifies the number of replicates in each column when constructing latinized designs; default * i.e. all in one column|
||Spatial model to use with a single-treatment-factor resolvable design (
||Decay parameter to use when
||Variate with two values specifying weightings for the main effects and for the interactions in factorial treatment structures; default
||Variate with three values specifying weightings for the within-row-and-column, between-row and between-column information; default has weight one for the within-row-and-column information, and the reciprocal of their numbers of levels for the rows and columns|
||Scalar or variate with two values specifying seeds for the random numbers used by CycDesigN to search for the best design and to randomize it – if a scalar is specified the same seed is used for both purposes; default 0 i.e. set automatically|
||Whether to put the design factors into a spreadsheet (
||A scalar or a variate containing up to three numbers defining the time in minutes to spend on the first phase, the second phase and the spatial phase of the search (if the 2nd or 3rd numbers are omitted they default to the maximum of those specified); default 1|
Number of randomizations to generate from the best design; default 1
CycDesigN is a package for the computer generation of experimental designs, which constructs optimal or near-optimal block and row-column designs; see the book Cyclic and Computer Generated Designs by John & Williams (1995). CycDesigN can also operate as a batch program, that can be called from within Genstat. This program is distributed with Genstat, and there are procedures to call the program, read its output back into Genstat, and form the relevant design factors. There are also Genstat add-in and resource files to define user menus, which can be downloaded from the VSNi website. However, before CycDesigN can be used, a license must be obtained; see vsni.co.uk/software/cycdesign for details about the CycDesigN software.
CDNROWCOLUMNDESIGN, uses the CycDesigN algoriths to form a row-column design. The treatment factors, whose values are to be formed, are specified by the
TREATMENTFACTORS option. This can be set to a single factor if you want a one-way treatment structure. Alternatively, if option
NGROUPS is set, you can supply two factors to define a nested model
factor_1 / factor_2
The group sizes (i.e. the number of levels of the second factor within each level of the first factor) are supplied by
NGROUPS, in a variate. Otherwise, if option
NGROUPS is not set, you can supply from two to four factors, to define a factorial model.
LEVELS option can be used to define the numbers of levels of the factors, as a scalar if there is only one factor, or as a variate if there are several. The levels specified in the variate are assumed to be in the same order as the order in which the factors occur in the
LEVELS can be omitted if the factors have already been been declared with the right numbers of levels. Alternatively, if you want only a single treatment factor, and do not want to save its generated levels, you can specify its number of levels using
LEVELS, and leave
NROWS option can define the number of rows, and the
ROWS option can supply a factor to save the levels generated for the row factor. You can omit
ROWS is set to a factor that has already been defined with the correct number of levels. Similarly, the
NCOLUMNS option can define the number of columns, and the
COLUMNS option can supply a factor to save the levels generated for the column factor. Finally, the
NREPLICATES option can define the number of replicates of each treatment combination, and the
REPLICATES option can supply a factor to save the levels generated for a replication factor.
Printed output is controlled by the
||to print the design,|
||to print a report by CycDesigN on the design, and|
||to print the factor values.|
RESOLVABLE option controls whether or not the design is resolvable i.e. whether the rows and columns can be grouped into replicates, each of which contains a single replicate of each treatment combination. Suppose that there are v treatment combinations, k rows, s columns and r replicates of each treatment combination. Then in a non-resolvable design these numbers must satisfy the condition
v × r = k × s
whereas in a resolvable design the condition is
v = k × s.
By default the design search has a single stage. However, you can use the
METHOD option to request that two stages are used. The first constructs the column component design, and second forms the row-column design. (At the second stage the column component design is not changed; this is achieved by allowing only treatment interchanges to take place within columns.) If
METHOD=unrestrictedtwostage, there is no restriction on the way in which the design is constructed during the first stage. Alternatively, if
METHOD=twostage, an alpha design is constructed during the first stage for a resolvable design, or a cyclic design is constructed during the first stage for a non-resolvable design.
You can set option
NRLATIN to request that the design is latinized by rows. If
NRLATIN=1, the replication of each treatment combination is equalized as far as possible within each row. Alternatively, setting
NRLATIN to n, say, aims to equalize the occurrence of the treatment combinations within each set of n contiguous rows. Similarly option
NCLATIN can request that the design is latinized by columns. By default, the replicates in a latinized design are assumed to be in a single row, side by side. The
REPLATINGROUPS option allows you to to define an alternative layout. For example, setting
REPLATINGROUPS=!(1,2) when you have three replicates, defines two columns of replicates, the first with one replicate (replicate 1), and the second with two replicates (replicate 2 alongside replicate 1, and replicate 3 below replicate 2).
SPATIALMODEL option lets you request that the construction of a resolvable design should take account of the separation of different treatments in rows and columns. The principle is that plots close together are assumed to be correlated more than plots further apart; a spatial model attempts to model this correlation decay. The criterion used to generate spatial designs is the neighbour efficiency factor of Williams (1985), which has been extended to two-dimensional blocking structures by Williams, John & Whitaker (2005) and to cater for different decay functions. The available settings are
||modified second difference, and|
||modified exponential variance.|
The weights used with the first three settings are described by Williams (1985). The fourth setting,
ev, is appropriate for a model specifying an autoregressive variance matrix. Its decay parameter is specified by the
EVDECAY option; default 0.5. However, the spatial designs generated by CycDesigN are usually quite robust to the choice of weight function. Spatial models cannot be used with latinized designs.
WEIGHTS option and the
RCWEIGHTS option specify how to weight the importance of the information in the design.
WEIGHTS is used when the design has a factorial treatment structure, and
RCWEIGHTS is used when there is a single treatment factor or a nested treatment structure.
WEIGHTS option specifies a variate with two values to define how to weight the efficiencies of the terms when there is a factorial treatment structure. The first value defines a weight for the main effects (default 1), and the second defines a weight for the interactions (default 0.25) These defaults are the same as those used in the stand-alone CycDesigN system.
For designs without a factorial treatment structure, the
RCWEIGHTS option specifies a variate with three values to define the weightings to use for the within-row-and-column, between-row and between-column information. By default, the within-row-and-column information is given a weight of one, the between-row information has a weight equal to the reciprocal of the number of levels of the row factor, and the between-column information has a weight equal to the reciprocal of the number of levels of the column factor. These defaults are again the same as those in the stand-alone CycDesigN system.
SEED option lets you supply seeds for the random numbers to be used within CycDesigN to search for the best design and to randomize it. You can specify a variate with two values to supply a different seed for each purpose, or a scalar to use the same one for both. If a zero value is specified, the corresponding seed is set automatically. The default is the scalar zero.
By default only one randomization is done with the best design. However, you can use the
NRANDOMIZATION option to provide several randomizations of that design, for use in different trials. The
TRIALS option can save a factor to identify the trials.
You can set option
SPREADSHEET=design to put the design factors into a Genstat spreadsheet.
TIMELIMITS option can be set to a scalar or a variate containing up to three numbers to define the time in minutes to spend on the first phase, the second phase and the spatial phase of the design search. If the second or third numbers are omitted, they default to the maximum of those specified. The default is 1.
The batch program CycDesRun is called using the
John, J.A. & Williams, E.R. (1995). Cyclic and Computer Generated Designs. London: Chapman and Hall.
Williams, E.R. (1985). A criterion for the construction of optimal neighbour designs. J.R. Statist. Soc. B, 47, 487-497.
Williams, E.R., John, J.A. & Whitaker, D. (2005). Construction of resolvable spatial row-column designs. Biometrics, 62, 103-108.
CAPTION 'CDNROWCOLUMNDESIGN example'; STYLE=meta FACTOR [LEVELS=25] treat FACTOR [LEVELS=5] row FACTOR [LEVELS=10] column FACTOR [LEVELS=2] rep CDNROWCOLUMNDESIGN [PRINT=design; TREATMENT=treat;\ REPLICATES=rep; ROWS=row; COLUMNS=column;\ RESOLVABLE=no; SEED=38417; TIMELIMITS=0.2]