R help - Feb 2014 - Which analysis for a set of dummy variables alone ?

Dear R-users,

I have a dataset I would like to analyze and plot
It consists of 100 dummy variables (0/1) for about 2,000,000 observations
There is absolutely no quantitative variable, nor anything I could use as
an explained variable for a regression analysis.

Actually, the dataset represents the patronage of 2 billion customers for
100 stores. It equals 1 if the consumer go to the store, 0 if he doesn't.
With no further information.

As the variable look like factors (0/1), I thought I could go for a
Mutliple Correspondence Analysis (MCA). However, the resulting plot
consists of 2 points for each variable (one for 1 and one for 0) which is
not easily interpretable. (or is there a method for not plotting certain
points in MCA?)

I also tried to consider my dataset as a bipartite network
(consumer-store). However, the plot is not really insightful, as I am
especially looking for links between stores. (kind of "if a consumer go to
that store, he probably also goes to this one...")

So, I have a simple question: which method you would choose for computing
and plotting the links between a set of dummy variable?

Thanks in advance

Sylvain
PhD Marketing
Associate Professor University of Lille - FR

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This sounds more like a statistics question than an R question.  You may
have better luck posting to a different forum, e.g., Cross Validated,
http://stats.stackexchange.com/.

Jean


On Tue, Feb 4, 2014 at 3:19 AM, sylvain willart
<sylvain.willart@gmail.com>wrote:
> Dear R-users,
>
> I have a dataset I would like to analyze and plot
> It consists of 100 dummy variables (0/1) for about 2,000,000 observations
> There is absolutely no quantitative variable, nor anything I could use as
> an explained variable for a regression analysis.
>
> Actually, the dataset represents the patronage of 2 billion customers for
> 100 stores. It equals 1 if the consumer go to the store, 0 if he
doesn't.
> With no further information.
>
> As the variable look like factors (0/1), I thought I could go for a
> Mutliple Correspondence Analysis (MCA). However, the resulting plot
> consists of 2 points for each variable (one for 1 and one for 0) which is
> not easily interpretable. (or is there a method for not plotting certain
> points in MCA?)
>
> I also tried to consider my dataset as a bipartite network
> (consumer-store). However, the plot is not really insightful, as I am
> especially looking for links between stores. (kind of "if a consumer
go to
> that store, he probably also goes to this one...")
>
> So, I have a simple question: which method you would choose for computing
> and plotting the links between a set of dummy variable?
>
> Thanks in advance
>
> Sylvain
> PhD Marketing
> Associate Professor University of Lille - FR
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@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.
>
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