## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(simulateDCE) library(rlang) library(formula.tools) ## ----initialize--------------------------------------------------------------- # pass beta coefficients as a list bcoeff <- list( bpreis = -0.01, blade = -0.07, bwarte = 0.02 ) manipulations <- list( alt1.x2 = expr(alt1.x2 / 10), alt1.x3 = expr(alt1.x3 / 10), alt2.x2 = expr(alt2.x2 / 10), alt2.x3 = expr(alt2.x3 / 10) ) # place your utility functions here ul <- list( u1 = list( v1 = V.1 ~ bpreis * alt1.x1 + blade * alt1.x2 + bwarte * alt1.x3, v2 = V.2 ~ bpreis * alt2.x1 + blade * alt2.x2 + bwarte * alt2.x3 ), u2 = list( v1 = V.1 ~ bpreis * alt1.x1, v2 = V.2 ~ bpreis * alt2.x1 ) ) ## ----decision----------------------------------------------------------------- decisiongroups <- c(0, 0.7, 1) ## ----other-------------------------------------------------------------------- designpath <- system.file("extdata", "SE_DRIVE", package = "simulateDCE") resps <- 120 # number of respondents nosim <- 2 # number of simulations to run (about 500 is minimum) destype <- "ngene" ## ----output------------------------------------------------------------------- sedrive <- sim_all( nosim = nosim, resps = resps, designtype = destype, designpath = designpath, u = ul, bcoeff = bcoeff, decisiongroups = decisiongroups ) ## ----accessOutput------------------------------------------------------------- ## nested results are hard coded, if the design changes this must aswell simulationCoeff <- sedrive$olddesign$coefs coeffSummary <- sedrive$olddesign$summary print(simulationCoeff) print(coeffSummary)