I am using the mlogit function from the mlogit package to run a multinomial logit regression. I am not sure how to add interaction terms into my model. Here is a toy dataset and my attempt to add interactions:
library(mlogit)
data <- data.frame(y=sample(1:3, 24, replace = TRUE),
x1 = c(rep(1,12), rep(2,12)),
x2 = rep(c(rep(1,4), rep(2,4), rep(3,4)),2),
x3=rnorm(24),
z1 = sample(1:10, 24, replace = TRUE))
m0 <- mlogit(y ~ 0|x1 + x2 + x3 + z1, shape = "wide", data = data) #model with only main effects
m1 <- mlogit(y ~ 0|(x1 + x2 + x3 + z1)^2, shape = "wide", data = data) #model assuming with all possible 2-way interactions?
The output from summary(m1) shows:
Coefficients :
Estimate Std. Error z-value Pr(>|z|)
(Intercept):2 86.41088 164.93831 0.5239 0.6003
(Intercept):3 62.43859 163.57346 0.3817 0.7027
x1:2 -32.27065 82.62474 -0.3906 0.6961
x1:3 0.24661 84.07429 0.0029 0.9977
x2:2 -75.09247 81.36496 -0.9229 0.3561
x2:3 -85.16452 81.40983 -1.0461 0.2955
x3:2 113.11778 119.15990 0.9493 0.3425
x3:3 112.77622 117.74567 0.9578 0.3382
z1:2 11.18665 22.32508 0.5011 0.6163
z1:3 13.15552 22.26441 0.5909 0.5546
x1:2 34.01298 39.66983 0.8574 0.3912
x1:3 32.19141 39.48373 0.8153 0.4149
x1:2 -53.86747 59.75696 -0.9014 0.3674
x1:3 -47.97693 59.09055 -0.8119 0.4168
x1:2 -6.98799 11.29920 -0.6185 0.5363
x1:3 -10.41574 11.52313 -0.9039 0.3660
x2:2 0.59185 6.68807 0.0885 0.9295
x2:3 2.63458 4.94419 0.5329 0.5941
x2:2 0.80945 2.03769 0.3972 0.6912
x2:3 2.60383 2.21878 1.1735 0.2406
x3:2 -0.64112 1.64678 -0.3893 0.6970
x3:3 -2.14289 1.98436 -1.0799 0.2802
the first column is not quite clear to me what specific interactions were outputted. Any pointers will be greatly appreciated!
This might be a clearer way to do it:
library(dplyr)
library(broom)
library(nnet)
multinom(formula = y ~ (x1 + x2 + x3 + z1)^2, data = data) %>%
tidy()
# A tibble: 22 x 6
y.level term estimate std.error statistic p.value
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 2 (Intercept) -158. 247. -0.640 0.522
2 2 x1 -388. 247. -1.57 0.116
3 2 x2 -13.4 248. -0.0543 0.957
4 2 x3 120. 334. 0.360 0.719
5 2 z1 173. 968. 0.179 0.858
6 2 x1:x2 337. 248. 1.36 0.174
7 2 x1:x3 40.2 334. 0.120 0.904
8 2 x1:z1 -53.8 968. -0.0555 0.956
9 2 x2:x3 -137. 1018. -0.135 0.893
10 2 x2:z1 -76.6 910. -0.0841 0.933
# … with 12 more rows