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dc.contributor.authorEideh, Abdulhakeem A. H.
dc.date.accessioned2018-08-26T09:59:02Z
dc.date.available2018-08-26T09:59:02Z
dc.date.issued2012-07-25
dc.identifier.citationAbdulhakeem A. H. Eideh (2012): Fitting Variance Components Model and Fixed Effects Model for One- Way Analysis of Variance to Complex Survey Data, Communications in Statistics - Theory and Methods, 41:16-17, 3278-3300en_US
dc.identifier.issn1532-415X
dc.identifier.urihttps://dspace.alquds.edu/handle/20.500.12213/784
dc.description.abstractUnder complex survey sampling, in particular when selection probabilities depend on the response variable (informative sampling), the sample and population distributions are different, possibly resulting in selection bias. This article is concerned with this problem by fitting two statistical models, namely: the variance components model (a two-stage model) and the fixed effects model (a single-stage model) for one-way analysis of variance, under complex survey design, for example, two-stage sampling, stratification, and unequal probability of selection, etc. Classical theory underlying the use of the two-stage model involves simple random sampling for each of the two stages. In such cases the model in the sample, after sample selection, is the same as model for the population; before sample selection. When the selection probabilities are related to the values of the response variable, standard estimates of the population model parameters may be severely biased, leading possibly to false inference. The idea behind the approach is to extract the model holding for the sample data as a function of the model in the population and of the first order inclusion probabilities. And then fit the sample model, using analysis of variance, maximum likelihood, and pseudo maximum likelihood methods of estimation. The main feature of the proposed techniques is related to their behavior in terms of the informativeness parameter. We also show that the use of the population model that ignores the informative sampling design, yields biased model fitting.en_US
dc.description.sponsorshipThe author is grateful to Gad Nathan, to the Associate Editor and to the referees for constructive comments and suggestions that helped improving the quality of the article.en_US
dc.language.isoen_USen_US
dc.publisherTaylor & Francisen_US
dc.subjectFixed effects modelen_US
dc.subjectInformative samplingen_US
dc.subjectMaximum likelihood estimationen_US
dc.subjectPseudo maximum likelihooden_US
dc.subjectSample distributionen_US
dc.subjectVariance components modelen_US
dc.titleFitting Variance Components Model and Fixed Effects Model for One-Way Analysis of Variance to Complex Survey Dataen_US
dc.typeArticleen_US


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