Question

在嵌套的logit模型中，您可以在树的每个级别定义回归量。在我在手册和其他示例中阅读的所有示例中，回归量仅针对最后一级进行定义。我将使用一个常见的例子，捕鱼模式。

巢：

Shore = { Beach, Pier} , Boat = { Charter, Private}

假设我有回归量Price，CatchRate和Income。如何使用Price和CatchRate解释最后一级，Income解释第一级。

在R中，我可以这样做：

mlogit(choice~price+catch,nests=list(shore=c("pier","beach"),boat=c("charter","private")))

但我不知道在哪里粘贴变量income。

Answer 1

您正在使用的示例和问题的答案都在文档中：

## model with charter as the reference level

m <- mlogit(mode ~ price+ catch | income, data = Fish, reflevel = "charter")

## same model with a subset of alternatives : charter, pier, beach

m <- mlogit(mode ~ price+ catch | income, data = Fish,
            alt.subset = c("charter", "pier", "beach"))

## a pure "multinomial model"

summary(mlogit(mode ~ 0 | income, data = Fish))

## which can also be estimated using multinom (package nnet)

library("nnet")
summary(multinom(mode ~ income, data = Fishing))

## a "mixed" model

m <- mlogit(mode ~ price+ catch | income, data = Fish)
summary(m)

mlogit包R：关于嵌套Logit

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