choiceDes (version 0.9-3)

dcm.design.cand: Optimal fractional factorial design

Description

Generate an optimal restricted fractional factorial design given a pre-generated candidate set.

Usage

dcm.design.cand(cand, nb, sets, alts, fname=NULL, Rd=20, print=TRUE)

Arguments

cand

A data frame of columns representing factors in the design OR a tab-delimited file readable using read.table(filename). If cand is not a data frame, an external file is assumed.

nb

The number of blocks or versions in the final design.

sets

The number of choice sets in each version of the final design.

alts

The number of alternatives in each choice set.

fname

A character string, usually ending in ".txt", indiciating the name of the file containing the levels-coded design.

Rd

The number of repeats used by the initial design and blocking algorithms. See arg nRepeats in optFederov and optBlock for additional details

print

Boolean indicating whether there is output to the console during execution.

Value

levels

A data frame consisting of the levels-coded design with blocks stacked in order. Variables for card, version and task are appended.

effects

A list of the effects-coded, blocked design and diagnostics. See optBlock for additional details.

d.eff

A list containing D efficiency, the variance-covariance matrix, and parameter standard deviations from the effects-coded design. See dcm.design.effcy for additional details.

Details

Generates balanced and blocked choice sets from a pre-generated candidate set. Typical use will involve (1) generating a full factorial candidate set (see gen.factorial), (2) manipulating levels as desired (e.g., adding restrictions) and, (3) using the manipulated set as input into the function.

Design optimization and blocking use the same algorithms as those in dcm.design.

If fname is not NULL a tab-delimited plain-text file is generated in the working directory containing the levels-coded design.

References

Federov, V.V. (1972). Theory of optimal experiments. Academic Press, New York.

Wheeler, R.E. (2004). AlgDesign. The R project for statistical computing. (http://www.r-project.org).

See Also

dcm.design, optFederov, optBlock

Examples

# NOT RUN {
## generate full factorial candidate set
cand <- gen.factorial(c(3,3,4), factors="all")

## restrict the candidate set so that level 3 in the first factor 
## cannot occur with level 1 in the second factor
remove.rows <- which(cand[,1] == 3 & cand[,2] == 1)
cand.restr <- cand[-remove.rows,]

## generate the design from the restricted candidate set
## and check that no design rows violate the restriction
des <- dcm.design.cand(cand.restr, 10, 6, 2)
which(des$levels[,4] == 3 & des$levels[,5] == 1)
# }