Generate a Standard Design

Design

This gives the available design types. These are:

One-way Design (no Blocking)
A single treatment factor is used replicated a number of times with no restrictions on the treatment allocations to units.

One-way Design (in Randomized Blocks)
A single treatment factor is used replicated a number of times arranged so that every treatment occurs once within a block of units.

Two-way Design (no Blocking)
Two treatment factors are used in a factorial arrangement (every combination of the two factors is used), replicated a number of times with no restrictions on the treatment allocations to units.

Two-way Design (in Randomized Blocks)
A factorial combination of two treatment factors is used, replicated a number of times and arranged so that every treatment occurs once within a block of units.

General Treatment Structure (no Blocking)
Up to six treatment factors are used in a factorial arrangement (every combination of the factors is used), replicated a number of times, with no restrictions on the treatment allocations to units.

General Treatment Structure (in Randomized Blocks)
A factorial combination of up to six treatment factors is used, replicated a number of times and arranged so that every treatment combination occurs once within a block of units.

Completely Randomized Design
This is equivalent to the item General Treatment Structure (no Blocking).

Split-Plot Design
A factorial combination of two treatment factors, arranged in replicates with the added restriction that one of the treatments is added to groups of units (the whole plots), and then each level of the other factor is assigned within to units (the sub-plots) within the whole plots

Latin Square
A single treatment factor is allocated to a square arrangement of units such that each treatment occurs once within each row and column. The number of rows and columns therefore equals the number of treatment groups. The rows and columns may not present a spatial layout, but may be any pair of factors whose factorial combination that divide the units into groups of size 1.

Graeco-Latin Square
A Latin Square with a second superimposed treatment factor so that every level of the new factor occurs once in each row and column, and that every factorial combination of the two factors occurs once.

Split-Split-Plot Design
A design with three levels of nesting of the allocation of three treatment factors. The main plot factor is allocated to whole plots. Within each whole plot, one of each level of the sub-plot factor is allocated to sub-plots. Within each sub-plot, one of each level of the sub-sub-plot factor is allocated to sub-sub-plots.

General Split-Plot Design
A generalization of the split-plot design where factorial combinations of treatment factors can be allocated to either whole plots or sub-plots.

Lattice Design
A spatial design where treatment levels are optimally allocated to blocks of plots within a replicate to minimize the confounding between the blocks and the treatment effects. The number of treatment levels must be a perfect square (e.g. 9,25,36,49...) and is equal to the square of the number of blocks within a replicate.

Strip-plot (or Criss-cross) Design
This generates a design for up to 4 treatment factors. The design is arranged in replicates, each of which consists of a row-by-column array of plots. All combinations of the levels of some of the treatment factors are applied to complete columns within each replicate, and all combinations of the other treatments are applied to complete rows within each replicate. (The design is thus similar to the general split-plot design, except that there are "whole plots" running in two perpendicular directions.)

No. of treatment factors

For designs, where there various number of treatment factors can be handled, this specifies the number of treatments to be used in a factorial combination.

Sub-plot Treats

For the General Split-Plot Design, this specifies the number of treatment factors that are applied at the sub-plot level. This must be between 1 and the number of treatment factors − 1.

Factor Name

The name to be used for this factor.

Number of levels

The number of classes or levels that the factor is to have. For some designs this depends on other factors and so is shown but cannot be changed independently.

Replications Required

This opens a dialog that allows you to calculate the number of replicates required to detect a response of a given size with a given probability of detection, variance parameters and confidence level.

Check Power

Allows you to calculate the power for the chosen design, i.e. for a given level of response between two treatment groups and confidence level, it will calculate the probability of that can be detecting this response.

Unit Labels

When selected a set of labels to index the units of the design will be created in the structure whose name is provided in the associated edit box.

Randomize Design

When selected, the design will be randomized, otherwise the units will be in standard order.

Display design in a spreadsheet

If this is selected, the resulting design will be put into a spreadsheet window. The resulting spreadsheet will contain all the statements required to analyse the results from the design using the Analyse Spreadsheet Columns menu. Also if you open the Stats | Analysis of Variance | General menu from the spreadsheet, then the TREATMENTS and BLOCKS items will be completed for you using the General Analysis of Variance design choice.

Number of units

This is an informational label indicating how many units the current design will have.

Randomization Seed

This is automatically changed every time is a design is produced. If this is reset to a particular value used in a previous design, you will obtain the identical design a second time (i.e. units will have the same factor combinations). If providing your own seed, it should be a large integer (i.e. > 9999).

Action Buttons

Run	Generate the design.
Cancel	Close the menu without further changes.
Options	Opens a dialog where additional options and settings can be specified for the designs. For example, the options include methods for modifying the basic designs (extra replication of a treatment, two way factorial combination with added control) and the form of unit labels generated (if the unit labels option is selected).
Defaults	Set the menu settings back to the default settings. Clicking the right mouse on this button produces a pop-up menu where you can choose to set the menu using the currently stored defaults or the GenStat default settings.