Fitting general linear model for longitudinal survey data under informative sampling
Date
2010-12-10
Authors
Eideh, Abdulhakeem A.H.
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Abstract
The purpose of this article is to account for informative sampling in fitting
superpopulation model for multivariate observations, and in particular
multivariate normal distribution, for longitudinal survey data. The idea behind the
proposed approach is to extract the model holding for the sample data as a
function of the model in the population and the first order inclusion probabilities,
and then fit the sample model using maximum likelihood, pseudo maximum
likelihood and estimating equations methods. As an application of the results, we
fit the general linear model for longitudinal survey data under informative
sampling using different covariance structures: the exponential correlation model,
the uniform correlation model, and the random effect model, and using different
conditional expectations of first order inclusion probabilities given the study
variable. The main feature of the present estimators is their behaviours in terms of
the informativeness parameters.
Description
Keywords
General Linear Model , Informative sampling , Longitudinal Survey Data , Maximum Likelihood , Sample distribution