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Re: st: creating a numeric matrix from string variables


From   joe j <joe.stata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: creating a numeric matrix from string variables
Date   Mon, 8 Jun 2009 11:53:06 +0200

Hi Bill,

Thank you. I appreciate your detailed explanations. I understand that
your suggestion was apt if I were to do some sot of a pair-wise
analysis, which I don't intend to do immediately; but it's still great
to know.

Thanks again,
Joe.

On Fri, Jun 5, 2009 at 4:04 PM, William Gould, StataCorp
LP<wgould@stata.com> wrote:
> In the thread about using Mata to create a matrix of the number of
> agreements between firms, and in response to my last posting,
> Joe. J. said the first part was "exactly what I was looking for"
> and wondered politely why I had felt obligated to add the
> second part.  To remind you, in the final iteration of the first
> part, the resulting data looks like this,
>
>              +-------------------------------------------------+
>              | company   f_11A   f_11K   f_12Z   f_14T   f_21S |
>              |-------------------------------------------------|
>           1. |     11A       0       0       2       1       0 |
>           2. |     11K       0       0       1       0       1 |
>           3. |     12Z       2       1       0       1       1 |
>           4. |     14T       1       0       1       0       0 |
>           5. |     21S       0       1       1       0       0 |
>              +-------------------------------------------------+
>
> and in the part I felt obligated to add, I recorded the data like this:
>
>              +-----------------------------------+
>              | c1   c2   company1   company2   n |
>              |-----------------------------------|
>           1. |  1    2        11A        11K   0 |
>           2. |  1    3        11A        12Z   2 |
>           3. |  1    4        11A        14T   1 |
>           4. |  1    5        11A        21S   0 |
>           5. |  2    3        11K        12Z   1 |
>              |-----------------------------------|
>           6. |  2    4        11K        14T   0 |
>           7. |  2    5        11K        21S   1 |
>           8. |  3    4        12Z        14T   1 |
>           9. |  3    5        12Z        21S   1 |
>          10. |  4    5        14T        21S   0 |
>              +-----------------------------------+
>
> There were two reasons for my unasked-for suggestion.
>
> First, Joe mentioned something about merging in the characteristics of the
> firms and, looking at the first organization, that looked hard to do.
> Obviously, it would be easy to merge in the characteristics of one of the
> parties -- the one recorded in the variable company -- but what about the
> characteristics of the other parties?  In the first observation, for
> instance, also needed would be the characteristics of 12Z and 14T.
>
> That lead me to the second organization, where each observation records a pair
> of the parties and so that parties are on equal footing.  One could merge in
> characteristics of company1 and of company2 into the data easily.
>
> Second, I thought to myself, how would I analyze these data?  I should hasten
> to add that I am not an expert or at least have to reason to think that I am,
> since I don't even know the details of the problem.  Were those details
> revealed, I could prove I'm not an expert.  Anyway, I wasn't sure what I would
> do with these data in the first organization, but how to analyze them in
> the second organization seemed obvious to me.  I could use logistic or
> Poisson regression, or even a hurdle model.  To be explained would be whether
> (or how many) agreements there were between pairs of companies based on their
> characteristics and, presumably, interactions of their characteristics.
>
> -- Bill
> wgould@stata.com
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