Re: st: complex multilevel analysis

[Christian Deindl <deindl@soziologie.uzh.ch>]

I am familiar with books and papers on dyadic data like
Snijders & Kenny 1999 and Kenny, Kashy, & Cook 2006, but their approach 
is somewhat different and doesn't really suit my kind of data.
I have no knowledge of the methods applied by Peter Hoff.

All my dyadic data analysis are working fine.

I just recently started with triadic data and I've never seen a paper on 
it.
So I try to follow the methods in dealing with cross classified date as 
described in Hox 2002 and mix it with the "Social Relation Model" from 
Snijders & Kenny 1999.

I am pretty sure that I'm close to a working solution, but something is 
still not quite right.

christian



Stas Kolenikov schrieb:
> I am personally pretty sure it is not quite right. But unfortunately I
> cannot claim I am a huge expert on dyadic and triadic data. I know
> there's been a couple of books out about analysis of dyadic data, but
> I've been most convinced by the work of Peter Hoff from U Washington
> who has thoroughly derived all those weird likelihoods that take into
> account all the necessary symmetries in the data. How familiar are you
> with those methods?
>
> On Wed, Dec 17, 2008 at 8:05 AM, Christian Deindl
> <deindl@soziologie.uzh.ch> wrote:
> > hi,
> >
> > I have a question regarding the analysis of triads using multilevel-models.
> >
> > I'm conducting an international comparison of financial transfers from
> > parents to their children.
> > each respondent can have up to four children, and each child is an
> > observation, with children nested within respondents nested within
> > households nested within countries.
> >
> > So I have four levels.
> > Since transfers are not only affected by the characteristics of children
> > but also by parents I 'm trying to analyse triads.
> >
> > the datastructure is as follows:
> >
> > Triad    Dyad(Parent)    Dyad(Child)    respondent
> > 1        mother1        child 1        1
> > 2        father1        child 1        1
> > 3        mother1        child 2        1
> > 4        father1        child 2        1
> > 1        mother2        child 1        2
> > 2        father2        child 1        2
> > 3        mother2        child 2        2
> > 4        father2        child 2        2
> > .        .        .
> > .        .        .
> >
> >
> > two problems in regard to mulitlevel-analysis arise with this structure.
> > 1) each child is doubled for each parent and for each respondent
> > 2) parents are doubled with children, but unique for each respondent
> >
> > as far as I know this is a case of cross-classification.
> >
> > to deal with the nonindependence of children and parents I build a dummy
> > variable for children (1 for the first appearance, zero for any further
> > appearance) and for parents.
> > this dummy-variables are included in the modell as random slopes for the
> > respondents (see syntax below).
> >
> > since I couldn't find a clear expamle in the literature I'm not quite
> > sure if I'm correct.
> >
> > Can anyone give me some advice?
> >
> > best regards,
> >
> > christian
> >
> >
> >
> > *Syntax:
> >
> > gen     dumkind=1
> > replace    dumkind=0 if dyadKINDER==dyadKINDER[_n-1] & persid==persid[_n-1]
> >
> > gen     dumeltern=1
> > replace    dumeltern=0 if dyad_e==dyad_e[_n-2] & persid==persid[_n-2]
> >
> >
> > xtmelogit   transfer_k  /*
> > */ || land:  || hhid: || persid:  dumkind dumeltern,  or
> >
> >
> > *
> > *   For searches and help try:
> > *   http://www.stata.com/help.cgi?search
> > *   http://www.stata.com/support/statalist/faq
> > *   http://www.ats.ucla.edu/stat/stata/

--
__________________
Christian Deindl
Universität Zürich
Soziologisches Institut
Andreasstr. 15
CH - 8050 Zürich
Tel: 0041/(0)44/635 23 46

http://www.suz.unizh.ch/ages
*
*   For searches and help try:
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