使用mlogit R函数时出错:两个索引未定义唯一的观察值

问题描述

我在R中使用mlogit函数时遇到了问题.我的数据集看起来像这样:

I've got a problem with the mlogit funtion in R. My dataset looks like this:

personID    caseID   altID    choice   a1    a2    a3    a4  
   1          1        1         1      3     0     3     1
   1          1        2         0      1     3     0     1
   1          1        3         0      4     4     4     4
   1          2        1         0      2     2     1     3
   1          2        2         1      2     3     1     3
etc....

我尝试运行以下代码，执行模型.

I've tried running the following code, performing the model.

setV2 <- mlogit.data(data = setV2, choice = "choice", shape = "long", alt.var = "altID", chid.var = "personID")
m <- mlogit(choice ~ a1 + a2 + a3 + a4 | -1, rpar = c(a1 = "n", a2 = "n", a3 = "n", a4 = "n"), correlation = FALSE, halton = NA, TM)

但是，我收到以下错误(在代码的第一行之后):

However, I receive the following error (after the first line of code):

Error in dfidx::dfidx(data = data, dfa$idx, drop.index = dfa$drop.index,  : 
  the two indexes don't define unique observations

类似的问题:使用mlogit R函数时出错:两个索引没有定义唯一的观察结果"

你们中的任何一个都知道出了什么问题吗?预先感谢.

Does any of you have an idea what's going wrong?Thanks in advance.

推荐答案

您的数据样本不足以提供正确的解决方案.

Your data sample is insufficient to provide a correct solution.

1. 确保提供正确的索引变量.

mlogit.data()是 dfidx()函数的包装，该函数对索引有一些违反直觉的要求.您案例中的 caseID 应该针对所有特定案例而有所不同，而不是仅在单个 personID 中.不同的 personID 不应存在相同的 caseID .

The mlogit.data() is a wrapper for dfidx() function, which has some counterintuitive requirements for indexes. The caseID in your case should vary for all specific cases, rather than only within a single personID. There shouldn't exist identical caseID for different personID.

1. 验证每个选择集中您的替代品数量是否相同.

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