如何在R中解释choicemodelr(rhierMnlRwMixture)的输出 [英] How to interpret the output of choicemodelr (rhierMnlRwMixture) in R

问题描述

我刚刚开始使用R库"choicemodelr"，并成功获得了一些beta值作为解决方案.但是我不知道如何将这些值分配给特定的属性级别.结果，我只获得A1B1，A1B2，A1B3等的值.该通用输出通常如何连接到我的设计?

I just started using the R library 'choicemodelr' and succeded in getting some beta values as a solution. But I wonder how do I assign these values to the specific attribute-levels. As a result I only get values for A1B1, A1B2, A1B3,... etc. How does this generic output generally connect to my Design?

在文档中找不到提示.选择模型库libraray或与其连接的Bayesm库(rhierMnlRwMixture)均不可用.希望您能帮我解决这个问题.

Didn't find a hint in the documentation. Neither for the choicemodelr libraray, nor the bayesm library (rhierMnlRwMixture) to which it is connected to. I hope you can help me with this one.

预先感谢， 菲尔

为了说明这一点，一些代码和输出:

to illustrate this, some code and output:

# loading neccesary librarys
library(bayesm)
library(MASS)
library(lattice)
library(Matrix)
library(ChoiceModelR)
library(XLConnect)

#DATENSATZ:
setwd("C:/DATA/CBC/")   # set workingdirectory
.Workbook <- loadWorkbook("DataCBC-R2.xls")
data <- data.frame(readWorksheet(.Workbook, "DataCBC-R"))
remove(.Workbook)

#set parameter for calculation
R = 50000 #Total Iterations of the Markov Chain Monte Carlo
use = 100 #Iterations for Paramerter-Estimation

#Parameter of datainput
none = TRUE #TRUE, if the questionaire has a none-Option but is not coded in the data
xcoding = c(0,0,0,0,0,0,1,1) #0=nominal scale; 1=metric scale

#Parameter dataoutput
save = TRUE #TRUE saves the calculated parameters
keep = 500 #number of random parameter draws to save (thinnig Parameter)

mcmc = list (R=R, use=use)
options = list(none=none, save=save, keep=keep, restart=restart)

#final calculation of the betas
out = choicemodelr(data, xcoding, mcmc = mcmc, demos = demos, options = options, constraints = constraints)

响应A1B1 A1B2 A1B3 A1B4 A2B1 A2B2无
001 -2,56 -6,54 -18,49 27,59 -1,74 1,74 -1,94
002 -3,18 -6,52 -19,79 29,49 0,50 -0,50 -0,58

Resp A1B1 A1B2 A1B3 A1B4 A2B1 A2B2 NONE
001 -2,56 -6,54 -18,49 27,59 -1,74 1,74 -1,94
002 -3,18 -6,52 -19,79 29,49 0,50 -0,50 -0,58

希望这些信息能对您有所帮助.让我知道，如果您需要更多信息.

Hope that piece of information helps. Let me know, if you need further information.

推荐答案

在交叉验证(应放在第一位的位置)处找到完整答案:https://stats.stackexchange.com/questions/85362 /how-to-the-choice-choicemodelr-rhiermnlrwmixture-in-r/86102#86102

Find the complete answer at cross validated (where it should have been in the first place): https://stats.stackexchange.com/questions/85362/how-to-interpret-the-output-of-choicemodelr-rhiermnlrwmixture-in-r/86102#86102

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