R 中的营销选择建模
Elea McDonnell Feit
Assistant Professor of Marketing, Drexel University
类型牛奶巧克力、黑巧克力、果仁牛奶、果仁黑巧克力、白巧克力
品牌Dove、Ghirardelli、Godiva、Hershey's、Lindt
价格0.5、0.6、… 以 0.1 递增 …、3.9、4.0
choc_survey[choc_survey$Subject == 1 & choc_survey$Trial == 1, ]
Subject Trial Alt Type Brand Price 1 1 1 1 NA NA NA 2 1 1 2 NA NA NA 3 1 1 3 NA NA NA
# Setup your attributes and levels list attribs <- list(Type = c("Milk", "Dark", "White"), Brand = c("Cadbury", "Toblerone", "Kinder"), Price = 5:30 / 10) # Create all possible combinations of attributes all_comb <- expand.grid(attribs) nrow(all_comb) head(all_comb)
# Setup your attributes and levels list attribs <- list(Type = c("Milk", "Dark", "White"), Brand = c("Cadbury", "Toblerone", "Kinder"), Price = 5:30 / 10)
# Create all possible combinations of attributes all_comb <- expand.grid(attribs) nrow(all_comb) head(all_comb)
144 Type Brand Price 1 Milk Cadbury 0.5 2 Dark Cadbury 0.5 3 White Cadbury 0.5 4 Milk Toblerone 0.5 5 Dark Toblerone 0.5 6 White Toblerone 0.5
144
Type Brand Price 1 Milk Cadbury 0.5 2 Dark Cadbury 0.5 3 White Cadbury 0.5 4 Milk Toblerone 0.5 5 Dark Toblerone 0.5 6 White Toblerone 0.5
for (i in 1:100) { rand_rows <- sample(1:nrow(all_comb), size = 12 * 3) rand_alts <- all_comb[rand_rows, ] choc_survey[choc_survey$Subject == i, 4:6] <- rand_alts }
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