R中的联合（）函数

Question

联合函数的输出有问题。 我有 5 个属性，每个属性有 3 个级别，但是在输出中，从第三级的第二个属性开始，结果是 NA，我不知道我能做些什么来解决这个问题。 这是我的代码和联合函数的结果（img.输出联合函数）。

你能帮帮我吗？

alimentatie<-c("mancare gatita","fast food","amandoua in mod alternativ") 

activitati<-c("regulat","de cateva ori pe luna","foarte rar")

bauturi<-c("evit cat de mult pot","oricat de des simt nevoia","ocazional")

odihna<-c("7-8 ore","4-6 ore","mai mult de 8 ore")

Recreere<-c("3-6","mai mult de 6","mai putin de 3")

factor_levels<-as.data.frame(c(alimentatie,activitati,bauturi,odihna,recreere))

colnames(factor_levels)<-"levels"

data<-expand.grid(alimentatie,activitati,bauturi,odihna,recreere)

colnames(data)<-c("Alimentatie","Activitati","Bauturi","Odihna","Recreere")


facdesign_full<-caFactorialDesign(data = data, type = "full")

encdesign_full<-caFactorialDesign(facdesign_full)


response<-read.table("cc.txt", sep="\t",header = T)
response<-as.data.frame(response)


conjoint_analysis<-Conjoint(response,encdesign_full,factor_levels)

我将5个问题的每个答案（一共59个答案）编码为“0 1和2”的值为：

Alimentatie: "mancare gatita" code 0, "fast food" code 1 ,"amandoua in mod alternativ" code 2; 
Activitati: "regulat" code 0,"de cateva ori pe luna" code 1,"foarte rar" code 2; 
Bauturi: "evit cat de mult pot" code 0,"oricat de des simt nevoia" code 1 ,"ocazional" code 2; 
Odihna: "7-8 ore" code 0,"4-6 ore" code 1,"mai mult de 8 ore" code 2;
Recreere: "3-6" code 0,"mai mult de 6" code 1,"mai putin de 3" code  2

我附上了一张照片（数据），其中包含 cc.csv 文件的一部分（因为 txt 文件出现偏移）。

数据： Data Link

dput(rasps)
structure(list(`Profil 1` = c(0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
0L, 0L, 2L, 0L, 2L, 0L, 1L, 2L, 0L, 2L, 0L, 2L, 0L, 0L, 2L, 0L, 
2L, 0L, 0L, 0L, 2L, 2L, 2L, 0L, 0L, 0L, 0L, 2L, 0L, 2L, 0L, 0L, 
2L, 2L, 0L, 0L, 2L, 0L, 2L, 2L, 0L, 2L, 2L, 1L, 0L, 2L, 0L, 2L, 
2L, 0L, 1L), `Profil 2` = c(1L, 1L, 0L, 2L, 1L, 1L, 2L, 0L, 0L, 
0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 2L, 2L, 0L, 0L, 1L, 1L, 2L, 1L, 
2L, 0L, 0L, 2L, 1L, 1L, 0L, 0L, 1L, 0L, 2L, 1L, 2L, 2L, 1L, 1L, 
2L, 2L, 0L, 2L, 0L, 1L, 2L, 0L, 2L, 2L, 2L, 0L, 2L, 1L, 1L, 1L, 
2L, 2L), `Profil 3` = c(2L, 0L, 0L, 2L, 0L, 2L, 1L, 0L, 0L, 2L, 
1L, 1L, 0L, 0L, 1L, 2L, 2L, 2L, 0L, 2L, 0L, 0L, 2L, 2L, 1L, 2L, 
0L, 0L, 0L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 0L, 1L, 2L, 1L, 0L, 1L, 
2L, 0L, 1L, 0L, 2L, 2L, 1L, 1L, 2L, 1L, 0L, 2L, 2L, 1L, 1L, 0L, 
2L), `Profil 4` = c(0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 2L, 0L, 1L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
0L, 0L, 1L, 2L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 2L, 0L, 1L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 0L, 1L
), `Profil 5` = c(0L, 1L, 2L, 0L, 0L, 2L, 0L, 2L, 2L, 2L, 2L, 
0L, 0L, 0L, 1L, 2L, 0L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 0L, 2L, 
0L, 2L, 1L, 0L, 0L, 2L, 2L, 0L, 0L, 2L, 2L, 1L, 1L, 1L, 0L, 0L, 
2L, 0L, 1L, 0L, 0L, 2L, 2L, 2L, 2L, 0L, 2L, 0L, 0L, 0L, 2L, 2L
)), class = "data.frame", row.names = c(NA, 59L))

Data

更新代码后：

After Update

输出联合函数：

Answer 1

您的原始代码在两个连续的行中两次调用caFactorialDesign 函数。然而根据conjointvignette，caEncodedDesign是

[that] 对使用获得的因子设计进行编码的函数 caFactorialDesign 函数用于联合模块的需要 功能正常

基于此，我认为一个问题似乎是您的第二个caFactorialDesign 调用不正确。您可能应该改为调用caEncodedDesign 来生成encdesign_full 对象。因此，尝试将您的代码调整为：

    # replace the line encdesign_full <- caFactorialDesign(facdesign_full) with
    encdesign_full <- caEncodedDesign(facdesign_full)

另外，你的代码重写是一种更紧凑和可重现的方式：

    # load library
    library(conjoint)

    # combinations of levels
    data <- expand.grid(
      alimentatie = c("mancare gatita","fast food","amandoua in mod alternativ"), 
      activitati = c("regulat","de cateva ori pe luna","foarte rar"),
      bauturi = c("evit cat de mult pot","oricat de des simt nevoia","ocazional"),
      odihna = c("7-8 ore","4-6 ore","mai mult de 8 ore"),
      recreere = c("3-6","mai mult de 6","mai putin de 3"))

    # profile
    facdesign_full <- caFactorialDesign(data = data, type = "full")
    profile <- caEncodedDesign(facdesign_full)

    # level names
    levelnames <- data.frame(
      levels = c("mancare gatita","fast food","amandoua in mod alternativ",
      "regulat","de cateva ori pe luna","foarte rar","evit cat de mult pot",
      "oricat de des simt nevoia","ocazional", "7-8 ore","4-6 ore",
      "mai mult de 8 ore","3-6","mai mult de 6","mai putin de 3")
  )
# preferences
    response <- structure(list(alimentatie = c(0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
      0L, 0L, 2L, 0L, 2L, 0L, 1L, 2L, 0L, 2L, 0L, 2L, 0L, 0L, 2L, 0L, 
      2L, 0L, 0L, 0L, 2L, 2L, 2L, 0L, 0L, 0L, 0L, 2L, 0L, 2L, 0L, 0L, 
      2L, 2L, 0L, 0L, 2L, 0L, 2L, 2L, 0L, 2L, 2L, 1L, 0L, 2L, 0L, 2L, 
      2L, 0L, 1L), activitati = c(1L, 1L, 0L, 2L, 1L, 1L, 2L, 0L, 0L, 
      0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 2L, 2L, 0L, 0L, 1L, 1L, 2L, 1L, 
      2L, 0L, 0L, 2L, 1L, 1L, 0L, 0L, 1L, 0L, 2L, 1L, 2L, 2L, 1L, 1L, 
      2L, 2L, 0L, 2L, 0L, 1L, 2L, 0L, 2L, 2L, 2L, 0L, 2L, 1L, 1L, 1L, 
      2L, 2L), bauturi = c(2L, 0L, 0L, 2L, 0L, 2L, 1L, 0L, 0L, 2L, 
      1L, 1L, 0L, 0L, 1L, 2L, 2L, 2L, 0L, 2L, 0L, 0L, 2L, 2L, 1L, 2L, 
      0L, 0L, 0L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 0L, 1L, 2L, 1L, 0L, 1L, 
      2L, 0L, 1L, 0L, 2L, 2L, 1L, 1L, 2L, 1L, 0L, 2L, 2L, 1L, 1L, 0L, 
      2L), odihna = c(0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
      0L, 0L, 0L, 2L, 0L, 1L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
      0L, 1L, 2L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 2L, 0L, 1L, 0L, 0L, 
      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 0L, 1L), 
      recreere = c(0L, 1L, 2L, 0L, 0L, 2L, 0L, 2L, 2L, 2L, 2L, 
      0L, 0L, 0L, 1L, 2L, 0L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 0L, 
      2L, 0L, 2L, 1L, 0L, 0L, 2L, 2L, 0L, 0L, 2L, 2L, 1L, 1L, 1L, 
      0L, 0L, 2L, 0L, 1L, 0L, 0L, 2L, 2L, 2L, 2L, 0L, 2L, 0L, 0L, 
      0L, 2L, 2L)), class = "data.frame", row.names = c(NA, -59L))

请注意，通过指定“完整”设计，profile 对象有 243 行，而您的 response 对象只有 59：

dim(profile)
[1] 243 5
dim(response)
[1] 59 5

这似乎混淆了Conjoint 函数，我猜是因为它在response 对象中查找243 行数据。

实际上，如果将 184 行模拟数据附加到 response 对象，Conjoint 似乎会产生预期的结果：

    # simulated response data
    set.seed(1)
    response_sim <- data.frame(alimentatie = sample(0:2, 184, replace = T),
      activitati = sample(0:2, 184, replace = T),
      bauturi = sample(0:2, 184, replace = T),
      odihna = sample(0:2, 184, replace = T),
      recreere = sample(0:2, 184, replace = T))

    # append simulated preferences
    response_n243 <- rbind(response, response_sim)

    # run 
    Conjoint(response_n243,profile, levelnames)

结论

您的问题似乎是由于您的 response 对象中的数据少于运行“完整”因子设计所需的数据。似乎您可能需要提供更多 response 数据，或者重新考虑您的设计，特别注意 caFactorialDesign 的 type 参数。 “分数”设计可能是一种替代方案。