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Re: st: complex multilevel analysis


From   "Stas Kolenikov" <[email protected]>
To   [email protected]
Subject   Re: st: complex multilevel analysis
Date   Wed, 17 Dec 2008 12:25:57 -0600

There's a new book edited by Card, Selig and Little -- have you seen
it yet? Does it have any leads towards your kind of data?

Peter Hoff's web page is http://www.stat.washington.edu/hoff, there
are links to papers and R software.

On Wed, Dec 17, 2008 at 11:57 AM, Christian Deindl
<[email protected]> wrote:
> 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
>> <[email protected]> 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:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>



-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.

*
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