hassediagrams: generates the layout structure and restricted layout structure of experimental designs ================ Damianos Michaelides, Simon Bate, Marion Chatfield
The hassediagrams
package provides tools to visualize
the structure of experimental designs using Hasse
diagrams. The package determines the structure of the design, summarised
by the layout structure, and uses this structure to generate a Hasse
diagram. This diagram describes the structure of the design and the
relationships between the factors that define the design. By considering
the randomisation performed, in conjunction with the layout structure, a
list of randomisation objects can be identified, known as the restricted
layout structure. The package can also be used to generate a Hasse
Diagram of this restricted layout structure. Objects in the restricted
layout structure can be used to identify the terms to include in the
statistical model.
The package is an implementation of the methodology described in Bate and Chatfield (2016a and 2016b).
Bate S.T., Chatfield M.J. (2016a). “Identifying the structure of the experimental design.” Journal of Quality Technology, 48(4), 343–364.
Bate S.T., Chatfield M.J. (2016b). “Using the structure of the experimental design and the randomization to construct a mixed model.” Journal of Quality Technology, 48(4), 365–387.
hasselayout()
Creates a Hasse diagram of the layout structure. To generate the diagram all this is needed is a dataset consisting of the experimental factors that define the experimental design.
itemlist()
A function needed to generate the objects required to generate the Hasse diagram of the restricted layout structure
hasserls()
Creates the Hasse diagram of the restricted layout structure. Inputs
to the function are the rls
object, generated using the
itemlist() function, an object that defines the randomisation objects
and an object that defines the randomisation arrows.
The development version of hassediagrams
can be
installed with:
# Install devtools (if not already installed)
install.packages("devtools")
# Install hassediagrams from GitHub
::install_github("GSK-Biostatistics/hassediagrams") devtools
install.packages("hassediagrams")
Load the package:
library(hassediagrams)
hasselayout(datadesign=concrete, larger.fontlabelmultiplier=1.6,
smaller.fontlabelmultiplier=1.3, table.out="Y")
<- itemlist(datadesign=concrete) concrete_objects
<- concrete_objects$TransferObject
concrete_rls 2] <- concrete_rls[,1]
concrete_rls[,27,2] <- c("AC^AG^CC^CoT^CuT \u2192 Run") concrete_rls[
hasserls(object=concrete_objects, randomisation.objects=concrete_rls,
larger.fontlabelmultiplier=1.6, smaller.fontlabelmultiplier=1.3,
table.out="Y", arrow.pos=8)
For an introduction to the methodology, check the package vignette:
vignette("Introduction_to_hassediagrams")
and for an introduction to the package implementation visit the documentation.
This package is in a stable state and will only be updated for bug fixes.
The person responsible for monitoring this package is Simon Bate simon.t.bate@gsk.com.