augment_levels: Augment levels and B-matrix to Full Factorial Design.

In JedStephens/ExpertChoice: Design of Discrete Choice and Conjoint Analysis

Description

Augments the full factorial design with a column summarising the levels of that design. Importantly, it also adds the B-matrix as an attribute.

Usage

augment_levels(full_factorial)

Arguments

full_factorial

a 'data.table' generated from the 'full_factorial' function.

Value

a 'data.frame' with an additional column identifying the level and the B-matrix attribute.

References

Street, D. J.; Burgess, L. & Louviere, J. J. Quick and easy choice sets: Constructing optimal and nearly optimal stated choice experiments International Journal of Research in Marketing, 2005 , 22 , 459 - 470

Examples

# See Practical Introduction to ExpertChoice Vignette. Step 2.

#Step 1
attrshort  = list(condition = c("0", "1", "2"),
technical =c("0", "1", "2"),
provenance = c("0", "1"))

#Step 2! - the augment_levels function
#' # ff stands for "full fatorial"
 ff  <-  full_factorial(attrshort)
 af  <-  augment_levels(ff)
# af stands for "augmented factorial"
af
# Compare ff and af. - do not confuse them. They serve different purposes.

JedStephens/ExpertChoice documentation built on April 8, 2020, 2:57 p.m.