Description Usage Arguments Details Value Warning Note Author(s) References See Also Examples

This menu based function constructs simple experimental designs for repeated measurements with one or two block variables. It is assumed that each subject is assigned to each treatment at most once. A maximum number of subjects in the study is also requested. Five possible construction methods available. These construction methods and the characteristics of the resulting designs are described in Wakeling and MacFie (1995). See also Jones and Kenward (1989), Ch. 5, for a discussion of these designs. The function is demonstrated in more detail in Sailer (2005).

1 | ```
get.plan(trt, k = trt, maxsub = 1000)
``` |

`trt` |
An integer > 1, giving the number of treatments. |

`k` |
An integer in {2,..., |

`maxsub` |
The maximum number of subjects available. |

The five types of designs are: designs based on all possible treatment orders ("all.combin"),
Williams designs ("williams"), designs based on
mutually orthogonal latin squares ("des.MOLS"), a combination of balanced incomplete block designs (BIBDs) and Williams designs
("williams.BIB") by Patterson (1951) and
the balanced minimal designs of Afsarinejad ("balmin.RMD").
Some designs are only available for special combinations of treatment number and number of periods. Other designs
may require too many subjects. Therefore, the possible choices available for the submitted values of *trt*,
*k* and *maxsub*
are determined.
If there is no design available, the parameters may be changed interactively.
If more than one design type is available the user has to choose one. The minimum number of subjects required
for the designs is given and maybe a criterion for selecting a design. All types of designs are balanced for first-order carryover effects.
All types except the balanced minimal RMDs are also balanced block designs.
The user may want to construct a design for a multiple of the minimum number of subjects required to get closer
to the preferred number of subjects.
Once the design is chosen the design is displayed. In practice the
labels for the treatments and subjects should be randomized before the
design is used.
The treatments are numbered 1,...,*trt*. The entry *(i,j)*
of the design corresponds to the treatment the *i*-th subject gets in the *j*-th period.

A matrix representing the experimental design.

For the construction of designs that combine BIBDs with Williams designs, the function `find.BIB`

is called
to search for a BIBD. If the necessary conditions for the existence of a BIBD are fulfilled, this approach
always returns a design. This design will however not always be a BIBD!
When using the Patterson approach, please check the resulting design for balance using `isGYD`

and
`isCbalanced`

.

It should be noted that this is a computational problem only, not a problem of the theoretical approach of Patterson (1951).

The "All combinations" approach requires the package `gtools`

.

Oliver Sailer

Afsarinejad, K. (1983): Balanced repeated measurements designs. Biometrika 70, 199-204.

Jones, B. and Kenward, M.G. (1989): Design and Analysis of Cross-Over Trials. Chapman and Hall, London.

Patterson, H.D. (1951): Change-over trials. Journal of the Royal Statistical Society B 13, 256-271.

Patterson, H.D. (1952): The construction of balanced designs for experiments involving sequences of treatments. Biometrika 39, 32-48.

Sailer, O. (2005): crossdes: A package for design and randomization in crossover studies. Rnews 5, 24-27.

Wakeling, I.N. and MacFie, H.J.H. (1995): Designing consumer trials balanced for first and higher orders of carry-over effect when only a subset of k samples from t may be tested. Food Quality and Preference 6, 299-308.

Williams, E. J. (1949): Experimental designs balanced for the estimation of residual effects of treatments. Australian Journal of Scientific Research, Ser. A 2, 149-168.

`allcombs`

, `balmin.RMD`

, `des.MOLS`

,
`williams`

, `williams.BIB`

1 2 3 4 5 6 7 8 9 10 |

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