# Synthetic respondent data set: residents' valuation of rural environment conservation plan Data set artificially created for an example based on a BDCE design. This example illustrates residents' valuation of rural environment conservation plan. data ```r data(rural) ``` ## Format 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`). ## Author(s) Hideo Aizaki ## See Also `make.dataset`, `make.design.matrix`, `Lma.design`, `glm` ## Examples ```r 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) ```

rural dataset