FW: Regression: Multiple DV

[Anthony Babinec]

Fyi to the SPSS list -- Manmit has described an allocation model
that is easily handled in Latent Gold Choice from Statistical
Innovations.

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
Manmit Shrimali
Sent: Tuesday, March 20, 2007 10:26 PM
To: [hidden email]
Subject: Re: Regression: Multiple DV

Dan:

Thanks for your input. The problem is that currently sawtooth does not
offer CVA/HB for allocation type data. It takes only rating for one
dependent variable. I designed the survey in sawtooth and I already
tried that. If this would have been cbc then there r multiple options.
However, options are limited when we are talking about cva constant sum
chip allocation type data.

-----Original Message-----
From: Dan Zetu [mailto:[hidden email]]
Sent: Wednesday, March 21, 2007 8:53 AM
To: Manmit Shrimali; [hidden email]
Subject: Re: Regression: Multiple DV

Manmit:

You can run the allocation design using Hierarchical Bayes in Sawtooth
software. If you have used it before, you know that you will need to
generate a chs file which includes the design and allocations.  Sawtooth

will output respondent-level utilities which you can use to calculate
the
expected share of each drug. Unlike single-choice conjoint, you cannot
directly get the beta coefficients, but you will be able to generate an
Excel-like template to calculate expected shares for each drug.

Do you have access to Sawtooth software?

Dan

>From: Manmit Shrimali <[hidden email]>
>Reply-To: Manmit Shrimali <[hidden email]>
>To: [hidden email]
>Subject: Re: Regression: Multiple DV
>Date: Wed, 21 Mar 2007 08:07:08 +0530
>
>Paul:
>
>Thanks for your input. I did not generate the design from SPSS as spss
>cannot design the CVA allocation based design. Spss will not be able to
>analyze the multiple DV. I am also open to using other software but I
>need a base platform to begin with :-).
>
>Cheers,
>M
>
>-----Original Message-----
>From: [hidden email] [mailto:[hidden email]]
>Sent: Wednesday, March 21, 2007 8:00 AM
>To: Manmit Shrimali
>Cc: [hidden email]
>Subject: Re: Regression: Multiple DV
>
>Manmit,
>
>This is tough (only because I have not done this in spss).  In manova
>(between groups), you can generate beta-weights or parameters by

ticking

>parameter estimates before running the manova.  Running separate
>regressions? Why not the conjoint model in spss since this is how you
>have generated your design.  I am thinking this is a probit or logit
>type of analysis rather than a traditional regression (linear
>regression) because the dependent variable is not technically a
>continuous variable.
>
>There are other people on the list that could share further light on
>this.  Anthony Babinec (sorry to dob you in Anthony) has a way of
>adjusting the cox regression analysis to potentially maybe deal with
>your problem.  There are some internet links out there on using spss

for

>conjoing analysis.
>
>Best of luck
>
>Paul
>
>
> > Manmit Shrimali <[hidden email]> wrote:
> >
> > Hi Team:
> >
> >
> >
> > This is spss cum stat query. I was wondering if you experts help me
> > solve the following query:
> >
> >
> >
> > Background:
> >
> > I have collected the conjoint data. The design was CVA design i.e.
> > single concept at a time/per screen. Respondents had to allocate the
> > chips among 5 drugs summing to 10 chips. We randomly had shown 7

cards

> > out of 18 cards. Sample size is 196 respondents. We had four
>attributes
> > with three levels each.
> >
> >
> >
> > Query:
> >
> > Drugs will dependent variables and levels of attributes in conjoint
>card
> > will be independent variables. Therefore, we have multiple dependent
> > variables and multiple independent variables. I want to find out the
> > impact of independent variable on dependent variable and how IV
>affects
> > DV. I cannot take on one DV at a time and regress with IVs as DV

will

>be
> > having correlations with other DV - increase in prescription for one
> > drug will obviously reduce the prescription for other drugs which
>means
> > pure negative correlation.
> >
> >
> >
> > Is there any way I can use SPSS to solve the above query? Due to
>crunch
> > timeline I will greatly appreciate if you could reply at your
>earliest.
> > Using manova will simply tell me any difference exists in groups on
>DV.
> > However, I need to get beta coefficients so that I could translate

the
> > impact of each IV on DV. Some suggest that I do regression with one
DV
> > at a time with IV? Any thought on this?
> >
> >
> >
> > Please advice.
> >
> >
> >
> > Manmit

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