Question

我通过使用nnet包中的multinom（）函数在R中拟合多项式logit模型。我想回顾一下两组中每个班级的比例。如果我使用emmeans软件包，则会得到结果，如下所示。如果我使用打包车中的增量法，则得到相同的逆变换比例，但标准误差不同。我无法理解这种差异的原因。有人可以帮助我吗？预先非常感谢

##########################################################################
#load data
rm(list=ls())
freq <- c(21, 23, 17, 24, 19, 13, 34, 23, 21, 26, 29, 40, 37, 31, 23,
       32, 32, 22, 29, 28, 28, 33, 20, 34, 42, 45, 40, 42, 16, 7, 16,
       13, 28, 27, 25, 19, 33, 40, 37, 36, 47, 18, 20, 13, 12, 13, 13, 
       12, 40, 22, 33, 30, 15, 11, 8, 10, 26, 27, 21, 22, 30, 24, 31,
       30, 28, 25, 27, 21, 16, 24, 13, 8, 29, 12, 18, 8, 8, 4, 5, 4, 8,
       14, 16, 7, 27, 20, 13, 5, 20, 22, 14, 17, 13, 12, 20, 19, 14, 10,
       8, 3, 3, 10, 9, 1, 8, 8, 7, 10, 19, 15, 19, 20, 20, 13, 18, 11,
       21, 26, 22, 16)
Group <- rep(c("P1", "P2"), each = 12, length.out = length(freq))
Class <- rep( paste("c", 1:5, sep = ""), each=24)

datasetR <- data.frame(
  Photo = rep(rep(1:24, 5), times = freq), 
  Group = rep(Group, times = freq),
  Class = rep(paste("c", 1:5, sep = ""), times = c(639, 614, 542, 335, 311)) )
rm(freq, Group)

#Fit multinomial model
library(nnet)
mmod <- multinom(Class ~ Group, data=datasetR)

#Calculate proportions
library(emmeans)
emmeans(mmod, ~Class|Group, mode="prob")

#Use delta method to derive standard errors
library(car)
coefs <- as.vector(coef(mmod))
names(coefs) <- paste("b", 1:8, sep="")
vcovMmod <- vcov(mmod)
p1 <- deltaMethod(coefs, g="1/(1+(exp(b1)+exp(b2)+exp(b3)+exp(b4)))",   vcov.=vcovMmod)
p2 <- deltaMethod(coefs, g="exp(b1)/(1+(exp(b1)+exp(b2)+exp(b3)+exp(b4)))", vcov.=vcovMmod)
p3 <- deltaMethod(coefs, g="exp(b2)/(1+(exp(b1)+exp(b2)+exp(b3)+exp(b4)))", vcov.=vcovMmod)
p4 <- deltaMethod(coefs, g="exp(b3)/(1+(exp(b1)+exp(b2)+exp(b3)+exp(b4)))", vcov.=vcovMmod)
p5 <- deltaMethod(coefs, g="exp(b4)/(1+(exp(b1)+exp(b2)+exp(b3)+exp(b4)))", vcov.=vcovMmod)
p6 <- deltaMethod(coefs, g="exp(0)/(1+(exp(b1 +b5)+exp(b2+b6)+exp(b3+b7)+exp(b4+b8)))",  vcov.=vcovMmod)
p7 <- deltaMethod(coefs, g="exp(b1+b5)/(1+(exp(b1+b5)+exp(b2+b6)+exp(b3+b7)+exp(b4+b8)))", vcov.=vcovMmod)
p8 <- deltaMethod(coefs, g="exp(b2+b6)/(1+(exp(b1+b5)+exp(b2+b6)+exp(b3+b7)+exp(b4+b8)))", vcov.=vcovMmod)
p9 <- deltaMethod(coefs, g="exp(b3+b7)/(1+(exp(b1+b5)+exp(b2+b6)+exp(b3+b7)+exp(b4+b8)))", vcov.=vcovMmod)
p10 <- deltaMethod(coefs, g="exp(b4+b8)/(1+(exp(b1+b5)+exp(b2+b6)+exp(b3+b7)+exp(b4+b8)))", vcov.=vcovMmod)
result <- rbind(p1=p1,p2=p2,p3=p3,p4=p4,p5=p5,p6=p6,p7=p7,p8=p8,p9=p9,p10=p10)
result

基于多项式拟合的em数标准误差

0 个答案: