Bayesian analysis of Turkish Income and Living Conditions data, using clustered longitudinal ordinal modelling with Bridge distributed random effects

dc.contributor.authorAsar, Ozgur
dc.date.accessioned2023-02-21T12:32:20Z
dc.date.available2023-02-21T12:32:20Z
dc.date.issued2021-01-01
dc.description.abstractThis article is motivated by the panel surveys, called Statistics on Income and Living Conditions (SILC), conducted annually on (randomly selected) country representative households to monitor EU 2020 aims on poverty reduction. We particularly consider the surveys conducted in Turkey within the scope of integration to the EU. Our main interests are on health aspects of economic and living conditions. The outcome is self-reported health that is clustered longitudinal ordinal, since repeated measures of it are nested within individuals and individuals are nested within families. Economic and living conditions have been measured through a number of individual- and family-level explanatory variables. The questions of interest are on the marginal relationships between the outcome and covariates that we address using a polytomous logistic regression with Bridge distributed random effects. This choice of distribution allows us to directly obtain marginal inferences in the presence of random effects. Widely used Normal distribution is also considered as the random effects distribution. Samples from the joint posterior densities of parameters and random effects are drawn using Markov Chain Monte Carlo. Interesting findings from the public health point of view are that differences were found between the subgroups of employment status, income level and panel year in terms of odds of reporting better health.
dc.description.issue5
dc.description.issueOCT
dc.description.pages405-427
dc.description.volume21
dc.identifier.doi10.1177/1471082X20920122
dc.identifier.urihttps://hdl.handle.net/11443/1004
dc.identifier.urihttp://dx.doi.org/10.1177/1471082X20920122
dc.identifier.wosWOS:000535504000001
dc.publisherSAGE PUBLICATIONS LTD
dc.relation.ispartofSTATISTICAL MODELLING
dc.subjectbridge distribution
dc.subjectLatent variables
dc.subjectmultilevel data
dc.subjectrepeated measures
dc.subjectself-reported health
dc.titleBayesian analysis of Turkish Income and Living Conditions data, using clustered longitudinal ordinal modelling with Bridge distributed random effects
dc.typeArticle

Files

Collections