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# Re: st: Absolute beginners guide to Multivariate probit analysis using Stata 12

 From "JVerkuilen (Gmail)" To statalist@hsphsun2.harvard.edu Subject Re: st: Absolute beginners guide to Multivariate probit analysis using Stata 12 Date Tue, 13 Nov 2012 15:06:00 -0500

```On Tue, Nov 13, 2012 at 2:58 PM, Sharon Brody <brodysharon@yahoo.co.uk> wrote:
> I am new to Stata and new to statistics.
> I have a dataset from a survey of 12200 people that I need to analyse. I have worked out binary probit and ordered probit, but am struggling with Multivariate probit.
> I have 5 variables that I need to assess there correlation with each other but more importantly the relationships between these and the other variables in the dataset. (Simultaneous equations I think its called)
> These variables are: % food recycled, % glass recycled, % metal recycled, % paper recycled and % plastic recycled. Each variable is ranked 0 to 100%. I have put them into 5 groups of 0%, 1-25%, 26-50%, 51-75% and 76-100%. I have also created variables for Yes/No ie do you recycle - respondents saying yes are 1 and those saying no are 0. We also have the Sweights to add.

How skewed are the responses on the original scale? If they're not
very skewed, I'd skip using probit analysis or the discretization that
you have undertaken and analyze the responses using -xtmixed-, because
you have five outcomes repeated per person. It's quite likely,
however, that this is not true, in which case you are stuck with a
number of possibilities. Multilevel ordinal probit or logit can be
done using -gllamm-.

An alternative is to use ordinal logit and then pool using -suest-.
The kind of model you get is different as it's not individual level
the way that a multilevel model is, but depending on your purposes
that may be more appropriate.

How much missing data?

However, all that said, if you're new to statistics this kind of
analysis is relatively challenging, so you might want to enlist some
local talent.

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