Define "true" model parameters as normally-distributed. Used in the
simulateChoices()
function.
randN(mu = 0, sigma = 1)
mu | Vector of means, defaults to |
---|---|
sigma | Vector of standard deviations, defaults to |
A list defining normally-distributed parameters of the "true"
utility model used to simulate choices in the simulateChoices()
function.
library(conjointTools) # Define the attributes and levels levels <- list( price = seq(1, 4, 0.5), # $ per pound type = c('Fuji', 'Gala', 'Honeycrisp', 'Pink Lady', 'Red Delicious'), freshness = c('Excellent', 'Average', 'Poor') ) # Make a full-factorial design of experiment doe <- makeDoe(levels) # Re-code levels doe <- recodeDoe(doe, levels) # Make the conjoint survey by randomly sampling from the doe survey <- makeSurvey( doe = doe, # Design of experiment nResp = 2000, # Total number of respondents (upper bound) nAltsPerQ = 3, # Number of alternatives per question nQPerResp = 6 # Number of questions per respondent ) # Simulate choices based on a utility model with the following parameters: # - 1 continuous "price" parameter # - 4 discrete parameters for "type" # - 2 random normal discrete parameters for "freshness" data_mxl <- simulateChoices( survey = survey, obsID = "obsID", pars = list( price = 0.1, type = c(0.1, 0.2, 0.3, 0.4), freshness = randN(mu = c(0.1, -0.1), sigma = c(1, 2))) )