conjoint.estimation: conjoint.estimation

In jlopezsi/MDSConjoint: An implementation of metric and nonmetric conjoint models for marketing decisions

Description

This function computes the partworth of attribute levels for each respondent. Uses treatment effects; ratings is a data frame of clients (rows) by bundle rated (colums); bundles is a data frame of bundles (rows) by attributes (colums)

Usage

conjoint.estimation(ratings, bundles, design.l, rank = 0, rs = 0,
  conj.contrasts = "sum")

Arguments

ratings	a data frame with all clients' ratings
bundles	a data frame with all product profiles rated by clients
design.l	a list with the conjoint design (attributes and levels)
rank	if rank==1, then transform a ranking into utilities
rs	if rs=1, record individuals' coefficients, other wise not record
conj.contrasts	if conj.contrasts=="sum", then options(contrasts = c("contr.sum", "contr.poly")), otherwise, treatment

Value

conjoint.results.all the object returned by the function

Examples

data(MDSConjointData)
names(MDSConjointData)
osc<-MDSConjointData$osc
class(osc)
names(osc)
osc.conjoint <- conjoint.estimation(osc$ratings, osc$bundles, osc$design)
names(osc.conjoint)
# [1] "summary"     "fit"         "part.worths"  "prediction"
head(osc.conjoint$summary)
head(osc.conjoint$fit)
head(osc.conjoint$part.worths)
head(osc.conjoint$prediction)

jlopezsi/MDSConjoint documentation built on May 19, 2019, 12:48 p.m.