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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: gllamm with pweights |

Date |
Thu, 16 Jul 2009 11:28:03 -0500 |

Oh, I see. With 64 second level units, you are in a much better shape. I would probably have an urban/rural dummy as an explanatory variables for those second levels with -feq- option. If you sum up the weights, you are using the weights twice. And that's hardly a great idea: you are overcompensating for unequal probabilities of selection, if there were any. Were these states/ruran/urban areas selected via a sampling procedure? Or what you have is a complete list? In the latter case, you surely would need to specify unit weights at the second level. On the issue of weights in multilevel models, see: http://www.citeulike.org/user/ctacmo/article/711637, http://www.citeulike.org/user/ctacmo/article/850244, http://www.citeulike.org/user/ctacmo/article/3158754. There's probably more by now, but I am not tracking this literature very closely. On Thu, Jul 16, 2009 at 11:18 AM, Kanter, Rebecca<rkanter@jhsph.edu> wrote: > Hi Stan and statalist, > > Regarding my second level it is more than 2 values...as there are 32 states in the country...that makes 64 values (or areas/clusters that i illustrate via one variable called urstate...e.g. if urstate=1 it is the urban area of the 1st state and if urstate=33 it is the rural area of the 1st state and so on) if one divides each state into its urban and rural areas, respectively. Each one I want to take its own intercept and slopes etc to better account and visualize the urban and rural differences in the country.... > > Thus, is it better to sum the individual weights per urstate (1-64) or let all weights for this second level equal one and keep my individual pweights as is for the individual level (level 1)? > > Thanks so much, > Rebecca > ___________________________________________ > Rebecca M. Kanter > PhD Candidate > Johns Hopkins Bloomberg School of Public Health > Department of International Health > Center for Human Nutrition > ________________________________________ > From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Stas Kolenikov [skolenik@gmail.com] > Sent: Wednesday, July 15, 2009 7:14 PM > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: gllamm with pweights > > With just two values of the second level variable, you won't get any > sensible results. I'd suggest modeling this with fixed effects of > urban/rural location and interaction with other variables, where > applicable. > > Couple points on the data set up: if you don't have the second level > weights, you should assume they are equal to 1. Also, -collapse- with > a -merge- is an overkill, you could get the sum of weights by > > egen sum_of_weights = sum( weight ) > > Of course the first comment is the more important one than these two :)). > > On Wed, Jul 15, 2009 at 5:37 PM, Kanter, Rebecca<rkanter@jhsph.edu> wrote: >> Hi, >> >> I am running 2 level multi-level models using gllamm. Level one is individuals and Level two is either the urban or rural part of the country's state (i.e. urstate). >> >> I would like to use the survey pweights I have...I only have pweights for the individual level (adul_sr), but it seems that you need pweights for all levels specified in gllamm (?) so this is what I did to create pweights for urstate based on these weights: >> >> collapse (sum) sadul_sr=adul_sr , by(urstate) >> >> then I merged them to the rest of my dataset >> >> and made this weight for the gllamm: >> >> *MLM-level pweights >> generate pwadulsr1=adul_sr >> *urstate summed adul_sr >> generate pwadulsr2=sadul_sr >> >> Then ran the most basic random-intercept only (around urstate) in gllamm and get the follow error below and am assuming it is a pweight problem but I do not know where the problem is coming from so if anyone has insight that would be much appreciated. Thanks so much! >> >> (note: diettag==1 & exwt==1 is the subpopulation i want to look at for this series of models) >> >> gllamm bmi2 if diettag==1 & exwt==1, i(urstate) pweight(pwadulsr) adapt nip(15) >> >> Running adaptive quadrature >> >> Convergence not achieved: try with more quadrature points >> >> >> ___________________________________________ >> Rebecca M. Kanter >> PhD Candidate >> Johns Hopkins Bloomberg School of Public Health >> Department of International Health >> Center for Human Nutrition >> >> * >> * 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. > > * > * 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/ > > * > * 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. * * 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/

**Follow-Ups**:**Re: st: gllamm with pweights***From:*sjsamuels@gmail.com

**RE: st: gllamm with pweights***From:*"Kanter, Rebecca" <rkanter@jhsph.edu>

**References**:**st: gllamm with pweights***From:*"Kanter, Rebecca" <rkanter@jhsph.edu>

**Re: st: gllamm with pweights***From:*Stas Kolenikov <skolenik@gmail.com>

**RE: st: gllamm with pweights***From:*"Kanter, Rebecca" <rkanter@jhsph.edu>

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