EvaluateDesign: Calculate efficiency measures for a given design

In idefix: Efficient Designs for Discrete Choice Experiments

Calculate efficiency measures for a given design

Description

This function calculates the following measures for a given design: AB-error, DB-error, standard deviations of the parameters, level frequency, level overlaps, and orthogonality.

Usage

EvaluateDesign(des, par.draws, n.alts, alt.cte = NULL, no.choice = FALSE)

Arguments

des	A design matrix in which each row is an alternative.
par.draws	A matrix or a list, depending on alt.cte.
n.alts	Numeric value indicating the number of alternatives per choice set.
alt.cte	A binary vector indicating for each alternative whether an alternative specific constant is present in the design. The default is NULL.
no.choice	A logical value indicating whether the design has a no choice alternative. The default is FALSE.

Details

The rules for specifying the function arguments are the same as in Modfed or CEA.

Alternative specific constants can be specified in alt.cte, if the design has any. The length of this binary vector should equal n.alts, were 0 indicates the absence of an alternative specific constant and 1 the opposite.

par.draws should be a matrix in which each row is a draw from a multivariate distribution. However, if there are alternative specific constants in the specified design, then par.draws should be a list containing two matrices: The first matrix containing the parameter draws for the alternative specific constant parameters. The second matrix containing the draws for the rest of the parameters.

If the design has a no.choice alternative, then no.choice should be set to TRUE.

Value

AB.error	Numeric value indicating the A(B)-error of the design.
DB.error	Numeric value indicating the D(B)-error of the design.
SD	The standard deviations of the parameters. Calculated by taking the diagonal of the varcov matrix, averaged over all draws if a sample matrix was provided in par.draws.
level.count	The count of all levels of each attribute in the design.
level.overlap	The count of overlapping levels accross alternatives in every choice set in the design.
Orthogonality	Numeric value indicating the degree of orthogonality of the design. The closer the value to 1, the more orthogonal the design is.

Examples

des <- example_design
mu = c(-1, -1.5, -1, -1.5, 0.5, 1)
Sigma = diag(length(mu))
par.draws <- MASS::mvrnorm(100, mu = mu, Sigma = Sigma)
n.alts = 2
EvaluateDesign(des = des, par.draws = par.draws, n.alts = n.alts)

#Example with a no.choice alternative
des.nc <- nochoice_design
mu = c(0.2, -0.5, -1, -0.5, -1, 0.5, 1)
Sigma = diag(length(mu))
par.draws <- MASS::mvrnorm(100, mu = mu, Sigma = Sigma)
par.draws <- list(par.draws[,1], par.draws[,-1])
n.alts = 3
EvaluateDesign(des = des.nc, par.draws = par.draws, n.alts = n.alts,
   alt.cte = c(0,0,1), no.choice = TRUE)

idefix documentation built on April 4, 2025, 1:51 a.m.