importance.of.attributes: Computes the importance of producy attributes

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

Description

This function computes attributes' importance. First I prepare the list conjoint.results, after that I compute the sample's mean. It uses sum zero contrasts to estimate part worths; ratings is a data frame of clients (rows) by bundles rated (colums); bundles is a data frame of bundles (rows) by attributes (colums); design.l is a list with the conjoint design (attributes and levels) Frist we prepare data

Usage

importance.of.attributes(ratings, bundles, design.l, rank = 0)

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 attributs and their levels
rank	if rank==1, then transform a ranking into utilities

Value

conjoint.list a list with three data frames: 1) fit, with the model fited for each individual, 2) part.worths, with the estimated part worths for all individuals 3) imp, wiht the attributes' importance for each individual

Examples

data(MDSConjointData)
names(MDSConjointData)
names(MDSConjointData$osc)
osc<-MDSConjointData$osc
osc.imp<-importance.of.attributes(osc$ratings, osc$bundles, osc$design)
names(osc.imp)
head(osc.imp$fit)
head(osc.imp$part.worths)
head(osc.imp$imp)
names(MDSConjointData$tire)
tire<-MDSConjointData$tire
tire.imp<-importance.of.attributes(tire$ratings, tire$bundles, tire$design)
names(tire.imp)
head(tire.imp$fit)
head(tire.imp$part.worths)
head(tire.imp$imp)

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