[R] optFederov/AlgDesign - help avail?

paulandpen paulandpen at optusnet.com.au
Tue Apr 22 16:03:29 CEST 2008


I would suggest reading this attachment below.

http://support.sas.com/techsup/technote/ts722d.pdf

OptFedreov is the go for you, you are correct.

I don't know of anybody who has come up with design principles in choice 
modelling that apply to logit and probit models etc.

We all assume that what is good for linear models in principle,  is also 
good for choice models, even when the utilities we are estimating are 
non-linear.

I think it is important to recognise that d-efficiency is the best method of 
evaluation for choice designs and you should be aiming for an orthogonal 
array in your design as suggested in this article

if you are using traditional logit and MNL, please make sure you allow 
enough choices and enough cases to complete the choices, and also that your 
algorithms are geared towards repeated choices if you are using a stated 
preference approach where people are answering a number of choice 
alternatives

Bob Wheeler may be able to comment further, but i think you are on the right 
track

Thanks Paul

----- Original Message ----- 
From: "zubin" <binabina at bellsouth.net>
To: <r-help at r-project.org>
Sent: Monday, April 21, 2008 9:59 PM
Subject: [R] optFederov/AlgDesign - help avail?


> Hello, we are needing to generate optimal (Fractional) designs for
> discrete choice applications, where we will be using logistic regression
> or multinomial logit as the modeling technique.
>
> It looks like optFederov, in the AlgDesign package may work, but not
> sure if this algorithm works when the variable of interest is binary or
> nominal?
>
> Anyone who are experts in this area, anyone interested in consulting
> with us in this topic (if so, email me we can arrange)?
>
> Or can confirm/deny optFederov can work in the discrete case?
>
> thx!
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



More information about the R-help mailing list