mfa: Synthetic respondent data set: citizens' preferences for the...
In support.BWS: Tools for Case 1 Best-Worst Scaling

mfa	R Documentation

Synthetic respondent data set: citizens' preferences for the multifunctionality of agriculture

Description

Data set artificially created for an example based on a two-level OMED. This example illustrates citizens' preferences for the multifunctionality of agriculture: landscape, biodiversity, water use, land conservation, flood control, rural viability, food security, animal welfare, and cultural heritage.

Usage

data(mfa)

Format

A data frame with 100 respondents on the following 25 variables.

ID: Identification number of respondents.
B1: Item selected as the best in question 1.
W1: Item selected as the worst in question 1.
B2: Item selected as the best in question 2.
W2: Item selected as the worst in question 2.
B3: Item selected as the best in question 3.
W3: Item selected as the worst in question 3.
B4: Item selected as the best in question 4.
W4: Item selected as the worst in question 4.
B5: Item selected as the best in question 5.
W5: Item selected as the worst in question 5.
B6: Item selected as the best in question 6.
W6: Item selected as the worst in question 6.
B7: Item selected as the best in question 7.
W7: Item selected as the worst in question 7.
B8: Item selected as the best in question 8.
W8: Item selected as the worst in question 8.
B9: Item selected as the best in question 9.
W9: Item selected as the worst in question 9.
B10: Item selected as the best in question 10.
W10: Item selected as the worst in question 10.
B11: Item selected as the best in question 11.
W11: Item selected as the worst in question 11.
B12: Item selected as the best in question 12.
W12: Item selected as the worst in question 12.

Author(s)

Hideo Aizaki

Examples

# The following OA is generated using oa.design()
# in the DoE.base package:
#  set.seed(123)
#  oa.design(nfactors = 9, nlevels = 2)
sets.mfa <- cbind(
  c(1,2,1,2,2,1,2,2,1,1,1,2),
  c(2,1,2,1,2,1,2,2,1,1,2,1),
  c(1,2,1,1,2,1,2,1,2,2,2,1),
  c(1,2,2,2,1,2,2,1,1,1,2,1),
  c(2,2,2,1,1,1,2,1,2,1,1,2),
  c(1,1,2,2,1,1,2,2,2,2,1,1),
  c(2,1,1,2,2,2,2,1,2,1,1,1),
  c(2,1,1,2,1,1,2,1,1,2,2,2),
  c(2,2,1,1,1,2,2,2,1,2,1,1))
items.mfa <- c(
  "Landscape",
  "Biodiversity",
  "Water use",
  "Land conservation",
  "Flood control",
  "Rural viability",
  "Food security",
  "Animal welfare",
  "Cultural heritage")
bws.questionnaire(
  choice.sets = sets.mfa,
  design.type = 1,
  item.names = items.mfa)
data(mfa)
data.mfa <- bws.dataset(
  respondent.dataset = mfa,
  response.type = 1,
  choice.sets = sets.mfa,
  design.type = 1,
  item.names = items.mfa)
count.mfa <- bws.count(data = data.mfa)
count.mfa

support.BWS documentation built on March 31, 2023, 8:12 p.m.