Hello all, I am trying to apply a conjoint analysis in order to determine the best profile that captures the most preferred combination of levels of given categorical factors. For this a set of factors is given and initially a fractional factorial design has to be produced as a subset of all possible factor levels combinations, sufficient to estimate the main effects utilities. Then the preference for each chosen combination is assessed via surveys on subjects (clients). Preferences are given by ranking profiles ordinally. Conjoint analysis then is applied on the preference data to estimate the utility values - or the "part worth" for each factor level. SPSS 13.0 has a module called CONJOINT that handles such problem from designing the fractional factorial design to the conjoint analysis. What would be the best way to implement such analysis in R? Thank you. Jimmy Cela Decision Sciences InterContinental Hotels Group Inc Atlanta, GA USA
Hi, try package "MNP" for a starting point - which could be used for choice-based-conjoint! And here a paper which show you that a normal Conjoint design is nothing others than a regression analysis, which could ready easy used with little bit programming in R. www.sawtoothsoftware.com/download/techpap/ca*excel*.pdf regards, Christian>Hello all, > > >I am trying to apply a conjoint analysis in order to determine the best >profile that captures the most preferred combination of levels of given >categorical factors. > >For this a set of factors is given and initially a fractional factorial >design has to be produced as a subset of all possible factor levels >combinations, sufficient to estimate the main effects utilities. > >Then the preference for each chosen combination is assessed via surveys on >subjects (clients). Preferences are given by ranking profiles ordinally. > >Conjoint analysis then is applied on the preference data to estimate the >utility values - or the "part worth" for each factor level. > >SPSS 13.0 has a module called CONJOINT that handles such problem from >designing the fractional factorial design to the conjoint analysis. > >What would be the best way to implement such analysis in R? > >Thank you. > >Jimmy Cela > >Decision Sciences >InterContinental Hotels Group Inc >Atlanta, GA >USA > >______________________________________________ >R-help at stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > > >
Hi there Maybe you can find useful The isoreg {modreg} package which does Monotone regression. This is probably what you need to model your data. Nonetheless be aware you need to code properly your design matrix (use orthogonal polynomial codes) The difference in using MNP or ordered probit is that with Monotonic regression you will have individual partworths utilities. Then you may aggregate your data on an individual level analysis. Hope this helps Regards ********************************************** Massimiliano Marinucci http://personales.ya.com/max_mar/ Ph.D Candidate in Economics Fundamentos del Analisis Econ??mico II (Econom??a Cuantitativa) Facultad de CC.EE. Universidad Complutense Madrid Campus de Somosaguas Madrid - Spain ********************************************** -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Cela, Jimmy (IHG) Sent: martes, 07 de junio de 2005 12:18 To: 'r-help at stat.math.ethz.ch' Subject: [R] Conjoint in R Hello all, I am trying to apply a conjoint analysis in order to determine the best profile that captures the most preferred combination of levels of given categorical factors. For this a set of factors is given and initially a fractional factorial design has to be produced as a subset of all possible factor levels combinations, sufficient to estimate the main effects utilities. Then the preference for each chosen combination is assessed via surveys on subjects (clients). Preferences are given by ranking profiles ordinally. Conjoint analysis then is applied on the preference data to estimate the utility values - or the "part worth" for each factor level. SPSS 13.0 has a module called CONJOINT that handles such problem from designing the fractional factorial design to the conjoint analysis. What would be the best way to implement such analysis in R? Thank you. Jimmy Cela Decision Sciences InterContinental Hotels Group Inc Atlanta, GA USA ______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Hi, The conf.design package should help you handle the experimental design side of your problem. Depending on your application, it may be unwise to assume that main effects will be enough, as interactions can often turn out to be important (at least in my experience with discrete conjoint). Hope this helps, James On 7/06/2005 10:18 p.m., Cela, Jimmy (IHG) wrote:> Hello all, > > > I am trying to apply a conjoint analysis in order to determine the best > profile that captures the most preferred combination of levels of given > categorical factors. > > For this a set of factors is given and initially a fractional factorial > design has to be produced as a subset of all possible factor levels > combinations, sufficient to estimate the main effects utilities. > > Then the preference for each chosen combination is assessed via surveys on > subjects (clients). Preferences are given by ranking profiles ordinally. > > Conjoint analysis then is applied on the preference data to estimate the > utility values - or the "part worth" for each factor level. > > SPSS 13.0 has a module called CONJOINT that handles such problem from > designing the fractional factorial design to the conjoint analysis. > > What would be the best way to implement such analysis in R? > > Thank you. > > Jimmy Cela > > Decision Sciences > InterContinental Hotels Group Inc > Atlanta, GA > USA > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html-- James Reilly Department of Statistics, University of Auckland Private Bag 92019, Auckland, New Zealand
Another approach, not mentioned yet, is to use ace, in the acepack package. I have used this in an article (with Andy Gurmankin) coming out soon in Memory and Cognition, which I could send by email. It isn't obvious to me that this will (or that it won't) work with a fractional factorial design; my hunch is that it will work. Jon On 06/07/05 06:18, Cela, Jimmy (IHG) wrote: I am trying to apply a conjoint analysis in order to determine the best profile that captures the most preferred combination of levels of given categorical factors. For this a set of factors is given and initially a fractional factorial design has to be produced as a subset of all possible factor levels combinations, sufficient to estimate the main effects utilities. Then the preference for each chosen combination is assessed via surveys on subjects (clients). Preferences are given by ranking profiles ordinally. Conjoint analysis then is applied on the preference data to estimate the utility values - or the "part worth" for each factor level. -- Jonathan Baron, Professor of Psychology, University of Pennsylvania Home page: http://www.sas.upenn.edu/~baron
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