conjoint (version 1.42)

caEncodedDesign: Function caEncodedDesign encodes full or fractional factorial design

Description

Function caEncodedDesign encodes full or fractional factorial design. Function converts design of experiment to matrix of profiles.

Usage

caEncodedDesign(design)

Arguments

design

design of experiment returned by caFactorialDesign function

Author

Andrzej Bak ,

Tomasz Bartlomowicz

Department of Econometrics and Computer Science, Wroclaw University of Economics, Poland

References

Bak A., Bartlomowicz T. (2012), Conjoint analysis method and its implementation in conjoint R package, [In:] Pociecha J., Decker R. (Eds.), Data analysis methods and its applications, C.H.Beck, Warszawa, p.239-248.

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, p. 283-317.

Green P.E., Srinivasan V. (1978), Conjoint Analysis in Consumer Research: Issues and Outlook, "Journal of Consumer Research", September, 5, p. 103-123.

SPSS 6.1 Categories (1994), SPSS Inc., Chicago.

See Also

caFactorialDesign and caRecreatedDesign

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="orthogonal")
print(design)
code=caEncodedDesign(design)
print(code)
print(cor(code))