Analysis of multivariate ordinal data for longitudinal surveys: CS11-613/99-5E-PDF
part I /
"Longitudinal survey data may comprise of ordinal polytomous repeated observations and a set of multi-dimensional covariates, for a large number of individuals. One of the main goals of the longitudinal survey is to see what happens to individuals or households over time. More precisely, one may like to describe the marginal expectation of the ordinal polytornous outcome variable as a function of the covariates while accounting for the structural (cross-sectional) as well as longitudinal correlations. The structural correlations arise because of the polytomous nature of the response variable, and the longitudinal correlations arise because of the repeatation of the structurally correlated responses over time. In this report, we develop a robust longitudinal correlations structure based generalized estimating equations approach to deal with multivariate polytomous survey data. This we do to analyze longitudinal survey data, such as SLID data collected by Statistics Canada. Details are given for the construction of the mean vector and structural and longitudinal correla-tions that are used in the development of the estimating equations. The regression estimates, that is, the estimates of the covariate effects, are shown to be consistent for the corresponding regression parameters"--Abstract.
|Department/Agency||Statistics Canada. Methodology Branch.|
|Title||Analysis of multivariate ordinal data for longitudinal surveys|
|Subtitle||part I /|
|Series Title||Working paper ;|
|Publication Type||Series - View Master Record|
|Electronic Document|| |
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|Note||"SSMD-99-005 E." "Revised: February 25, 1999." Digitized edition from print [produced by Statistics Canada].|
|Number of Pages||29 p.|
|Departmental Catalogue Number||11-613E|
|Subject Terms||Surveys, Methodology|
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