library(tidyverse)
library(mlogit)
library(dfidx)
library(marginaleffects)
chocolate <- read_csv("https://www.andrewheiss.com/blog/2023/08/12/conjoint-multilevel-multinomial-guide/data/choco_candy.csv") %>%
mutate(
dark = case_match(dark, 0 ~ "Milk", 1 ~ "Dark"),
dark = factor(dark, levels = c("Milk", "Dark")),
soft = case_match(soft, 0 ~ "Chewy", 1 ~ "Soft"),
soft = factor(soft, levels = c("Chewy", "Soft")),
nuts = case_match(nuts, 0 ~ "No nuts", 1 ~ "Nuts"),
nuts = factor(nuts, levels = c("No nuts", "Nuts"))
)
chocolate_idx <- dfidx(
chocolate,
idx = list("subj", "alt"),
choice = "choice",
shape = "long"
)
model_chocolate_mlogit <- mlogit(
choice ~ dark + soft + nuts | 0 | 0,
data = chocolate_idx
)
# Manual predictions and averaging
preds_chocolate_mlogit <- predictions(
model_chocolate_mlogit,
newdata = datagrid(dark = unique, soft = unique, nuts = unique)
)
preds_chocolate_mlogit %>%
group_by(dark) %>%
summarize(avg_pred = mean(estimate))
#> # A tibble: 2 × 2
#> dark avg_pred
#> <fct> <dbl>
#> 1 Milk 0.0500
#> 2 Dark 0.200
# Automatic predictions and averaging
by <- data.frame(dark = c("Milk", "Dark"), by = c("Milk", "Dark"))
predictions(
model_chocolate_mlogit,
by = by
)
#> Error: Unable to compute predicted values with this model. You can try to
#> supply a different dataset to the `newdata` argument. This error was
#> also raised:
#>
#> <text>:2:0: unexpected end of input
#> 1: . ~ . | . | . |
#> ^
#>
#> Bug Tracker:
#> https://github.com/vincentarelbundock/marginaleffects/issuesThis used to work though and would show these results:
##
## Estimate Std. Error z Pr(>|z|) 2.5 % 97.5 % By
## 0.20 0.0316 6.32 <0.001 0.138 0.262 Dark
## 0.05 0.0316 1.58 0.114 -0.012 0.112 Milk
##
## Columns: estimate, std.error, statistic, p.value, conf.low, conf.high, by