simulateDCE (version 0.3.1)

simulate_choices: Simulate choices based on a data.frame with a design and respondents

Description

Simulate choices based on a data.frame with a design and respondents

Usage

simulate_choices(
  data,
  utility,
  setspp,
  bcoeff,
  decisiongroups = c(0, 1),
  manipulations = list(),
  preprocess_function = NULL
)

Value

a data.frame that includes simulated choices and a design

Arguments

data

a dataframe that includes a design repeated for the number of observations

utility

a list with the utility functions, one utility function for each alternatives

setspp

an integer, the number of choice sets per person

bcoeff

List of initial coefficients for the utility function. List content/length can vary based on application. I ideally begins (but does not have to) with b and need be the same as those entered in the utility functions

decisiongroups

A vector showing how decision groups are numerically distributed

manipulations

A variable to alter terms of the utility functions examples may be applying a factor or applying changes to terms selectively for different groups

preprocess_function

= NULL You can supply a function that reads in external data (e.g. GIS coordinates) that will be merged with the simulated dataset. Make sure the the function outputs a data.frame that has a variable called ID which is used for matching.

Examples

example_df <- data.frame(
  ID = rep(1:100, each = 4),
  price = rep(c(10, 10, 20, 20), 100),
  quality = rep(c(1, 2, 1, 2), 100)
)

beta <- list(
  bprice   = -0.2,
  bquality =  0.8
)

ut <- list(
  u1 = list(
    v1 = V.1 ~ bprice * price + bquality * quality,
    v2 = V.2 ~ 0
  )
)
simulate_choices(example_df, ut, setspp = 4, bcoeff = beta)