# Package library("support.CEs") # Example 1: Unlabeled Design des1 <- rotation.design(attribute.names = list( Region = c("Reg_A", "Reg_B", "Reg_C"), Eco = c("Conv.", "More", "Most"), Price = c("1", "1.1", "1.2")), nalternatives = 2, nblocks = 1, row.renames = FALSE, randomize = TRUE, seed = 987) des1 questionnaire(choice.experiment.design = des1) data("syn.res1") syn.res1[1:3,] desmat1 <- make.design.matrix(choice.experiment.design = des1, optout = TRUE, categorical.attributes = c("Region", "Eco"), continuous.attributes = c("Price"), unlabeled = TRUE) desmat1[1:3,] dataset1 <- make.dataset(respondent.dataset = syn.res1, choice.indicators = c("q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9"), design.matrix = desmat1) dataset1[1:3,] clogout1 <- clogit(RES ~ ASC + Reg_B + Reg_C + More + Most + More:F + Most:F + Price + strata(STR), data = dataset1) clogout1 gofm(clogout1) mwtp(output = clogout1, monetary.variables = c("Price"), nonmonetary.variables = c("Reg_B", "Reg_C", "More", "Most", "More:F", "Most:F"), percentile.points = c(5, 95), seed = 987) # Example 2: Labeled Design des2 <- Lma.design(attribute.names = list( Eco = c("Conv.", "More", "Most"), Price = c("1", "1.1", "1.2")), nalternatives = 3, nblocks = 2, row.renames = FALSE, seed = 987) des2 questionnaire(choice.experiment.design = des2) data("syn.res2") syn.res2[1:3,] desmat2 <- make.design.matrix(choice.experiment.design = des2, optout = TRUE, categorical.attributes = c("Eco"), continuous.attributes = c("Price"), unlabeled = FALSE) desmat2[1:4,] dataset2 <- make.dataset(respondent.dataset = syn.res2, choice.indicators = c("q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9"), design.matrix = desmat2) dataset2[1:4,] clogout2 <- clogit(RES ~ ASC1 + More1 + Most1 + Price1 + ASC2 + More2 + Most2 + Price2 + ASC3 + More3 + Most3 + Price3 + strata(STR), data = dataset2) clogout2 gofm(clogout2) mwtp(output = clogout2, monetary.variables = c("Price1", "Price2", "Price3"), nonmonetary.variables = list( c("More1", "Most1"), c("More2", "Most2"), c("More3", "Most3")), percentile.points = c(5, 95), seed = 987)