## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(simulateDCE) library(rlang) library(formula.tools) ## ----initialize--------------------------------------------------------------- bcoeff <- list( bx1 = -0.1, bx2 = -0.1, bx3 = -0.05, bx4 = -0.025 ) # place your utility functions here ul <- list(u1 = list( v1 = V.1 ~ bx1 * alt1.x1 + bx2 * alt1.x2 + bx3 * alt1.x3 + bx4 * alt1.x4, v2 = V.2 ~ bx1 * alt2.x1 + bx2 * alt2.x2 + bx3 * alt2.x3 + bx4 * alt2.x4, v3 = V.3 ~ -5 )) ## ----other-------------------------------------------------------------------- designpath <- system.file("extdata", "CSA", "linear", package = "simulateDCE") ## can also be specified using relative path eg. designpath<- "Projects/CSA/Designs/" # notes <- "This design consists of different heuristics. One group did not attend the methan attribute, another group only decided based on the payment" notes <- "No Heuristics" resps <- 240 # number of respondents nosim <- 2 # number of simulations to run (about 500 is minimum) ## design type must be either 'spdesign' or 'ngene' destype <- "spdesign" ## ----random------------------------------------------------------------------- set.seed(3393) ## ----output------------------------------------------------------------------- csa <- simulateDCE::sim_all( nosim = nosim, resps = resps, designtype = destype, designpath = designpath, u = ul, bcoeff = bcoeff ) ## ----accessOutput------------------------------------------------------------- topLevelResults <- names(csa[sapply(csa, is.list)]) print(topLevelResults) ## saves and prints the key results of the first expreimental design simulationCoeff <- csa[[1]]$coefs coeffSummary <- csa[[1]]$summary print(simulationCoeff) print(coeffSummary) ## saveRDS(csa,file = "tests/manual-tests/csa.RDS")