Zobrazit minimální záznam
dc.contributor.author |
Labudová, Viera
|
|
dc.contributor.author |
Lakatová, Martina
|
|
dc.date.accessioned |
2019-01-03T14:06:39Z |
|
dc.date.available |
2019-01-03T14:06:39Z |
|
dc.date.issued |
2018 |
|
dc.identifier.issn |
1211-555X (Print) |
|
dc.identifier.issn |
1804-8048 (Online) |
|
dc.identifier.uri |
https://hdl.handle.net/10195/71993 |
|
dc.description.abstract |
The objective of this paper is to describe particularity of longitudinal data
and methods which can be used to analyse them. The assumption of usual tools used
for analysis is the independence of observations. In order to analyse of longitudinal
data, we have to make provisions for their particularity, which is the dependence of
observations. Therefore, while we analyse them, we must employ methods that are
adjusted to that dependence. Several approaches have been proposed to model binary
outcomes that arise from longitudinal studies. Most of the approaches can be grouped
into two classes: the population-averaged and subject-specific approaches. The
generalized estimating equations (GEE) method is used to estimate population
averaged effects. In this paper, we investigate the Generalized Estimating Equation
(GEE) capabilities of PROC GENMOD for correlated outcome data to fit models
using unspecified (unstructured) correlation structure. The data from EU SILC was
used to find out how material deprivation of households in the Slovak Republic
(material deprivation: yes (1), no (0)) is linked to their available characteristics. |
en |
dc.format |
p. 163 - 174 |
|
dc.language.iso |
sk |
|
dc.publisher |
Univerzita Pardubice |
cze |
dc.relation.ispartof |
Scientific papers of the University of Pardubice. Series D, Faculty of Economics and Administration. 44/2018 |
en |
dc.rights |
open access |
en |
dc.subject |
longitudinal data analysis |
en |
dc.subject |
material deprivation |
en |
dc.subject |
generalized estimating equation model |
en |
dc.subject |
EU SILC |
|
dc.title |
Model logistickej regresie pre longitudinálne údaje |
sk |
dc.title.alternative |
Logistic regression model for longitudinal data |
en |
dc.type |
Article |
en |
dc.peerreviewed |
yes |
en |
dc.publicationstatus |
published |
en |
dc.subject.jel |
C10 |
|
dc.subject.jel |
M31 |
|
dc.subject.jel |
O10 |
|
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