## SOCNET@LISTS.UFL.EDU

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Subject:

Re: statistics help

From:

Thomas W. Valente

Date:

Fri, 19 Apr 2002 10:07:15 -0700

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 ```Paul and others, The advice I've been given by many statisticians is to use GEE (General Estimating Equations) with no constraints on the correlation matrix (expectations of the degree of correlation within dyads). The other strategy has been to use the Sandwhich Estimator (Huber-White), both return similar results. In our paper on syringe sharing among needle exchange participants we had a cohort sample with egocentric network data. The cohort was uneven in that respondents varied in the number of followup interviews they had completed. We reshaped the data to be dyadic giving non-independence at 2 levels, the number of interviews and network. (Theoretically we might have been able to specify more covariation within respondents compared to within survey times, but mathematically this has not yet been implemented in any statistical package that I know of.) You can also use a general Multi- level model framework (also known as random effects model) specificing co-variation within respondents. Depending on the statistical package, someone can provide model examples (I use STATA mostly now). Statisticians may provide better and more complete answers. - Tom V. Paul Chung wrote: > Hi! As a network novice, I've run into a problem that I imagine most > socnetters have already successfully handled. > > I performed an analysis of the survey responses of 52 subjects, whom I > assorted into N*(N-1)/2 = 1326 unique dyads. My response variable was the > dyadic agreement in survey answers (measured on a scale), which I put into > an ordered logit regression. > > The problem, of course, is that these dyads, while unique, are not > independent, so my standard errors are wrong. Does anyone have an easy > solution to this problem? > > My e-mail address is below. If you feel that the question is of general > interest, please feel free to post your response. > > Thanks! Any help at all would be appreciated. I look forward to hearing from > you. > > Sincerely, > Paul Chung > > Email: [log in to unmask] -- To learn more about my evaluation book go to: http://www.oup-usa.org/isbn/0195141768.html Thomas W. Valente, PhD Director, Master of Public Health Program http://www.usc.edu/hsc/medicine/preventive_med/ipr/mph/ Department of Preventive Medicine School of Medicine University of Southern California 1000 Fremont Ave. Building A Room 5133 Alhambra CA 91803 phone: (626) 457-6678 fax: (626) 457-6699 email: [log in to unmask]```