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Re: st: Gllamm: Convergence not achieved: try with more quadrature points


From   Kjetil Arne Van Der Wel <kjetil.wel@sam.hio.no>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Gllamm: Convergence not achieved: try with more quadrature points
Date   Wed, 22 Sep 2010 09:29:47 +0200

Dear Steve,
Many thanks for this. Sorry for describing the analysis so poorly. I did actually run the command with pweight (I tried both methods), but that did not change the situation. Also, each country within the survey provides a representative sample of its population. Together, the countries constitutes EU-25, and hence, do not represent a greater *population' of countries. Furthermore, the countries are not merely administrative borders, but political entities employing different policies that have profound impact on the lives of their inhabitants. Because of this, I feel it is correct to treat them as 'units' in which individuals (and regions) are nested (i.e. appropriate entities of variation that can be described with variables) rather than 'strata' (which I take to mean as constructed by the researcher, such as social class). Sorry if I completely misunderstood you, Steve and Stas.

To give you a better idea of the problem: I am fitting a multilevel model to look at the effects of country-level variables on individual-level outcomes, as well as interaction effects between the country-level variables and individual characteristics (cross-level interactions). In the medical sociological and epidemiological literature, it is not unusual to publish results from multilevel analysis with as little 15-25 level 2 units (which are often European countries). Most analysts within this tradition use MLwiN. I first tried xtlogit to do my analysis (which works well), but it does not allow pweights or other weights that vary within level 2 units. This is why I wanted to have a go with gllamm, which seemed to be more flexible in regard to the weighting problem.

Running this command:

gllamm depvar indepvar1-4, i(country) pweight(wt) link(logit)

fam(binom) nip(20) adapt

leads to the error message, while omitting the pweight works fine. (By the way; depvar and all indepvars are binary individual level variables, except age. in the next model, continous counry level variables will be added).

If it does not work, I could report unweighted results from xtlogit:

xtlogit depvar age indepvar1-4(i) indepvar5-7(j) interactions terms(i*j), i(country) quad(20)

N(i)=188 000
N(j)=25

Is it possible to change the dataset according to the weights in advance of analysis, which could be a way around the problem?


Best,
Kjetil

On 21.09.2010 16:11, Steve Samuels wrote:
--
The -weight()- option in -gllamm- is intended to indicate frequency
weights. Use the -pweight()- option for probabilities. (It might make
no difference). I'm not expert in -gllamm-, but n = 27 countries looks
like a small number to me, especially if you have  country level
covariates. Please, as the FAQ request, show the actual command that
you issued.

As Stas states, countries are strata;  but you treat them as random.
You (probably) have enough observations to include country-specific
intercepts and slopes, which you can summarize as you please without
GLLAMM's strong assumptions of normal distributions and spatial
independence. You state that the design is not "complex"; I take this
to mean that individuals were selected within countries without
intermediate stages. Is this correct? In any case, a survey analysis
(-svyset-, followed by -svy: logistic- or -svy: logit-) might do all
that you need.


Steve

Steven J. Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax:    206-202-4783

2010/9/21 Kjetil Arne Van Der Wel<kjetil.wel@sam.hio.no>:
Dear all,
I am trying to run a logistic random intercept model with gllamm, using
sample weights. Whenever I include the pweight(wt) option I get the above
error message, but without the weights it works fine. I have tried
increasing nip (20, 30, 40), but it has been futile.

Level 2 units are 25 countries in Europe. Because they are not a sample, wt2
is set equal to 1. The level 1 sample weight (wt1), that corrects for
different sampling probabilities for individuals within different countries
(as well as country specific attrition), is entered
as specified by data supplier (non-integer, four digits or more).  The
weight was not scaled (as is otherwise suggested by the literature on
multilevel modelling of complex survey data (e.g. Rabe-Hesketh&  Skrondal,
2006)), because the sampling procedure was not ‘complex’,
i.e. level 2 units do not constitute a sample. Is this correct?

This is the gllamm command used:
gllamm depvar indepvar1 indepvar2, i(country) weight(wt) link(logit)
fam(binom) nip(20) iterate(20) adapt

My questions for you are:
1. Why do I get the error message and how to fix it?
2. Is my specification of the weights correct?

Thanks,
Kjetil van der Wel, PhD-student, Oslo University College



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--
Kjetil van der Wel
Stipendiat/PhD student
Gruppe for inkluderende velferd (GIV) / Research Group for Inclusive Social Welfare Policies,
Avdeling for samfunnsfag (SAM) / Faculty of social sciences
Høgskolen i Oslo / Oslo University College

Rom: SG304 (Stensberggata 29)
tlf/phone: +47 22 45 35 76 / +47 906 41 606
http://www.hio.no/giv

Postadresse/ postal address:
SAM
Høgskolen i Oslo
Postboks 4, St. Olavs plass
0130 Oslo


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