[R] Ordinal response model

[drlucyasher]

I have been asked to analyse some questionnaire data- which is not data I'm
that used to dealing with. I'm hoping that I can make use of the nabble
expertise (again).

The questionnaire has a section which contains a particular issue and then
questions which are related to this issue (and potentially to each other):
1) importance of the issue (7 ordinal categories from -3 to +3)
2) impact of the impact (7 ordinal categroies from -3 to +3)
3) percentage affected by the issue (11 ordinal categories from 0, 0-10,
20-30, 30-40.....90-100)
 
I also have three participant predictive factors:
Gender (M/F)
Age (continuous scale)
Sector (6 nominal categories)

So that my data looks like this:
    gen    age        sector impac importa percen
1     1     59          4     0      -3      2
2     2     64          3     2      -3      2
3     1     83          6     3      -3      2
4     1     66          5     2      -2      2
5     1     79          5     0      -1      2
6     2     63          4     0      -1      2

I have 2 questions I want my analysis to answer 
1) does gender/ age/ sector affect importance, impact, reponse
2) are importance/impact/response correlated in some way

I'm thinking I need some ordered logistic or probit model (possibly using
polr() command). The problem is the multivariate aspect- I need importance,
impact and perecentage in the same model to look at the covariance between
them and affects of gender, age and sector on these covariances.

It would be good to include a latent variable- at least for the perecentage
factor. 

Any help would be very much appreciated.
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