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I am trying to get the marginal effects from a multinomial model derived from the mlogit package but it shows an error. Can anyone provide some guidance to solve the problem? Many thanks!

# data
df1 <- structure(list(Y = c(3, 4, 1, 2, 3, 4, 1, 5, 2, 3, 4, 2, 1, 4, 
1, 5, 3, 3, 3, 5, 5, 4, 3, 5, 4, 2, 5, 4, 3, 2, 5, 3, 2, 5, 5, 
4, 5, 1, 2, 4, 3, 1, 2, 3, 1, 1, 3, 2, 4, 2, 2, 4, 1, 5, 3, 1, 
5, 2, 3, 4, 2, 4, 5, 2, 4, 1, 4, 2, 1, 5, 3, 2, 1, 4, 4, 1, 5, 
1, 1, 1, 4, 5, 5, 3, 2, 3, 3, 2, 4, 4, 5, 3, 5, 1, 2, 5, 5, 1, 
2, 3), D = c(12, 8, 6, 11, 5, 14, 0, 22, 15, 13, 18, 3, 5, 9, 
10, 28, 9, 16, 17, 14, 26, 18, 18, 23, 23, 12, 28, 14, 10, 15, 
26, 9, 2, 30, 18, 24, 27, 7, 6, 25, 13, 8, 4, 16, 1, 4, 5, 18, 
21, 1, 2, 19, 4, 2, 16, 17, 23, 15, 13, 21, 24, 14, 27, 6, 20, 
6, 19, 8, 7, 23, 11, 11, 1, 22, 21, 4, 27, 6, 2, 9, 18, 30, 26, 
22, 10, 1, 4, 7, 26, 15, 26, 18, 30, 1, 11, 29, 25, 3, 19, 15
), x1 = c(13, 12, 4, 3, 16, 16, 15, 13, 1, 15, 10, 16, 1, 17, 
7, 13, 12, 6, 8, 16, 16, 11, 7, 16, 5, 13, 12, 16, 17, 6, 16, 
9, 14, 16, 15, 5, 7, 2, 8, 2, 9, 9, 15, 13, 9, 4, 16, 2, 11, 
13, 11, 6, 4, 3, 7, 4, 12, 2, 16, 14, 3, 13, 10, 11, 10, 4, 11, 
16, 8, 12, 14, 9, 4, 16, 16, 12, 9, 10, 6, 1, 3, 8, 7, 7, 5, 
16, 17, 10, 4, 15, 10, 8, 3, 13, 9, 16, 12, 7, 4, 11), x2 = c(12, 
19, 18, 19, 15, 12, 15, 16, 15, 11, 12, 16, 17, 14, 12, 17, 17, 
16, 12, 20, 11, 11, 15, 14, 18, 10, 14, 13, 10, 14, 18, 18, 18, 
17, 18, 14, 16, 19, 18, 16, 18, 14, 17, 10, 16, 12, 16, 15, 11, 
18, 19, 15, 19, 11, 16, 10, 20, 14, 10, 12, 10, 15, 13, 15, 11, 
20, 11, 12, 16, 16, 11, 15, 11, 11, 10, 10, 16, 11, 20, 17, 20, 
17, 16, 11, 18, 19, 18, 14, 17, 11, 16, 11, 18, 14, 15, 16, 11, 
14, 11, 13)), class = "data.frame", row.names = c(NA, -100L))

library(mlogit)
mld <- mlogit.data(df1, choice="Y", shape="wide")  # shape data for `mlogit()`
mlfit <- mlogit(Y ~ 1 | D + x1 + x2, reflevel="1", data=ml.d)  # fit the model
effects(mlfit) # this shows the following error:
Error in if (rhs %in% c(1, 3)) { : argument is of length zero
Called from: effects.mlogit(mlfit)
cliu
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1 Answers1

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I believe you are missing the covariate information that needs to be put there, so if you use effects(mlfit, covariate = 'D'), It should work. Now the error is coming because the default of covariate is NULL. NULL is special in R, it has no(zero) length and hence you are getting argument of length zero. Please let me know if it fixes your issue.

As per documentation of effects.mlogit , it says:

covariate 
the name of the covariate for which the effect should be computed,

I am getting this output at my end:

R>effects(mlfit, covariate = 'D')
              1               2               3 
-0.003585105992 -0.070921137682 -0.026032167377 
              4               5 
 0.078295227196  0.022243183855
PKumar
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    Okay, great. Thank you @PKumar! – cliu Apr 07 '21 at 16:14
  • @cliu, All the best – PKumar Apr 07 '21 at 16:14
  • Hi @PKumar, just a quick followup question: I tried to extract the marginal effects for all the coefficients in the model but now it gave me the same error even if I specified the covariate. Do you know the way around it? Here is the code: `c.names <- names(ml.fit$model)[- c(1, 5:6)] ME.mnl <- sapply(c.names, function(x) stats::effects(mlfit, covariate='x', data=mld), simplify=FALSE)` Thank you for your help! – cliu Apr 07 '21 at 18:13
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    @cliu Run this: `sapply(c('D', 'x1', 'x2'), function(x)effects(mlfit, covariate = x))` also your model name is mlfit not ml.fit, c.names is giving you wrong result as there is no covariate in your equation named `linpred`, c.names should be this `c.names <- names(mlfit$model)[- c(1, 5:7)] ` – PKumar Apr 07 '21 at 18:34
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    Fabulous. Much appreciated @Pkumar! – cliu Apr 07 '21 at 21:33