rural | R Documentation |
Data set artificially created for an example based on a BDCE design. This example illustrates residents' valuation of rural environment conservation plan.
data(rural)
Data frames with 400 respondents on the following 7 variables.
ID
Identification number of respondents.
BLOCK
Serial number of blocks to which each respondent had been assigned.
q1
Response to choice experiment question 1.
q2
Response to choice experiment question 2.
q3
Response to choice experiment question 3.
q4
Response to choice experiment question 4.
Region
Region variable denoting whether the respondent was sampled from region 1 (Region = 1
) or region 2 (Region = 2
).
Hideo Aizaki
make.dataset
, make.design.matrix
, Lma.design
, glm
library(stats)
if(getRversion() >= "3.6.0") RNGkind(sample.kind = "Rounding")
d.rural <- Lma.design(
attribute.names = list(
Area = c("20", "40", "60", "80"),
Facility = c("None", "Agr", "Env", "Rec"),
Tax = c("1000", "3000", "5000", "7000")),
nalternatives = 1,
nblocks = 4,
row.renames = FALSE,
seed = 987)
common.alt <- c(Area = "0", Facility = "None", Tax = "0")
dm.rural <- make.design.matrix(
choice.experiment.design = d.rural,
optout = FALSE,
categorical.attributes = c("Facility"),
continuous.attributes = c("Area", "Tax"),
unlabeled = TRUE,
common = common.alt,
binary = TRUE)
data(rural)
rural1 <- subset(rural, Region == 1)
rural2 <- subset(rural, Region == 2)
ds.rural1 <- make.dataset(
respondent.dataset = rural1,
choice.indicators =
c("q1", "q2", "q3", "q4"),
design.matrix = dm.rural,
detail = FALSE)
ds.rural2 <- make.dataset(
respondent.dataset = rural2,
choice.indicators =
c("q1", "q2", "q3", "q4"),
design.matrix = dm.rural,
detail = FALSE)
fm.rural <- RES ~ Agr + Env + Rec + Area + Tax
out.rural1 <- glm(fm.rural,
family = binomial(link = "logit"),
data = ds.rural1)
summary(out.rural1)
out.rural2 <- glm(fm.rural,
family = binomial(link = "logit"),
data = ds.rural2)
summary(out.rural2)
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