conjoint (version 1.35)

caFactorialDesign: Function caFactorialDesign makes full or fractional factorial design

Description

Function caFactorialDesign makes full or fractional factorial design. Function can return orthogonal factorial design.

Usage

caFactorialDesign(data, type="null", cards=NA)

Arguments

data

experiment whose design consists of two or more factors, each with with 2 or more discrete levels

type

type of factorial design (possible values: "full", "fractional", "ca", "aca", "orthogonal"; default value: type="null")

cards

number of experimental runs

References

Bak A. (2009), Analiza Conjoint [Conjoint Analysis], [In:] Walesiak M., Gatnar E. (Eds.), Statystyczna analiza danych z wykorzystaniem programu R [Statistical Data Analysis using R], Wydawnictwo Naukowe PWN, Warszawa. Green P.E., Srinivasan V. (1978), Conjoint Analysis in Consumer Research: Issues and Outlook, "Journal of Consumer Research", September, 5, 103-123. SPSS 6.1 Categories (1994), SPSS Inc., Chicago.

See Also

caEncodedDesign

Examples

#Example 1
library(conjoint)
experiment = expand.grid(
price = c("low", "medium", "high"),
variety = c("black", "green", "red"),
kind = c("bags", "granulated", "leafy"),
aroma = c("yes", "no"))
design<-caFactorialDesign(data=experiment, type="full")
print(design)
print(cor(caEncodedDesign(design)))

#Example 2
library(conjoint)
experiment = expand.grid(
price = c("low", "medium", "high"),
variety = c("black", "green", "red"),
kind = c("bags", "granulated", "leafy"),
aroma = c("yes", "no"))
design<-caFactorialDesign(data=experiment)
print(design)
print(cor(caEncodedDesign(design)))

#Example 3
library(conjoint)
experiment = expand.grid(
price = c("low", "medium", "high"),
variety = c("black", "green", "red"),
kind = c("bags", "granulated", "leafy"),
aroma = c("yes", "no"))
design<-caFactorialDesign(data=experiment, type="fractional", cards=16)
print(design)
print(cor(caEncodedDesign(design)))

#Example 4
library(conjoint)
experiment = expand.grid(
price = c("low", "medium", "high"),
variety = c("black", "green", "red"),
kind = c("bags", "granulated", "leafy"),
aroma = c("yes", "no"))
design<-caFactorialDesign(data=experiment, type="fractional")
print(design)
print(cor(caEncodedDesign(design)))

#Example 5
library(conjoint)
experiment = expand.grid(
price = c("low", "medium", "high"),
variety = c("black", "green", "red"),
kind = c("bags", "granulated", "leafy"),
aroma = c("yes", "no"))
design<-caFactorialDesign(data=experiment, type="ca")
print(design)
print(cor(caEncodedDesign(design)))

#Example 6
library(conjoint)
experiment = expand.grid(
price = c("low", "medium", "high"),
variety = c("black", "green", "red"),
kind = c("bags", "granulated", "leafy"),
aroma = c("yes", "no"))
design<-caFactorialDesign(data=experiment, type="aca")
print(design)
print(cor(caEncodedDesign(design)))

#Example 7
library(conjoint)
experiment = expand.grid(
price = c("low", "medium", "high"),
variety = c("black", "green", "red"),
kind = c("bags", "granulated", "leafy"),
aroma = c("yes", "no"))
design<-caFactorialDesign(data=experiment, type="orthogonal")
print(design)
print(cor(caEncodedDesign(design)))