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1

A Longitudinal Study of Polish Attitudes to Emigration: A Latent Markov Model Approach

100%
Genge E.
Argumenta Oeconomica Cracoviensia
|
2017
|
issue 16
37-49
EN
Latent class analysis can be viewed as a special case of model-based clustering for multivariate discrete data. When longitudinal data are to be analysed, the research questions concern some form of change over time. The latent Markov model is a variation of the latent class model that is applied to estimate not only the prevalence of latent class membership, but the incidence of transitions over time in latent class membership. In 2004, Poland joined the European Union, prompting a number of Poles to leave the country. To examine this event, a model-based clustering approach for grouping and detecting inhomogeneities of public attitudes to emigration from Poland was used. It focuses especially on latent Markov models with covariates, which additionally made it possible to investigate the dynamic pattern of Poles’ attitudes to emigration for different demographic features. depmixS4, Rsolnp and LMest packages of R were used.
PL
Modele mieszanek, których składowe charakteryzowane są przez rozkłady prawdopodobieństw, reprezentują tzw. podejście modelowe w taksonomii. Obecnie coraz popularniejsze są modele mieszanek w analizie danych panelowych, w której celem jest już nie tylko podział obserwacji na homogeniczne grupy, ale również pewna analiza zmian w czasie. W takim przypadku stosowane są ukryte modele Markowa. W 2014 r. minęło 10 lat od przystąpienia Polski do Unii Europejskiej. Okres taki pozwala na dokonanie analizy nastawienia Polaków do emigracji. Celem badań jest podział Polaków na klasy o podobnym nastawieniu do emigracji w latach 2004–2013. Analiza empiryczna przeprowadzona została za pomocą ukrytych modeli Markowa z uwzględnieniem zmiennych towarzyszących. Wykorzystane zostały pakiety depmixS4, Rsolnp oraz LMest programu R.
2
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Graphical tools of discrete longitudinal data presentation in R

100%
Genge E.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2019
|
issue vol. 23 no. 3
26-39
EN
Good graphical presentation of data is useful during the whole analysis process from the first glimpse into the data to the model fitting and presentation of results. The most popular way of longitudinal data presentation are separate (for each wave, in cross-sectional dimension) comparisons of figures. However, plotting the data over time is useful in suggesting appropriate modeling techniques to deal with the heterogeneity observed in the trajectories. The main aim of this paper is to present the changing perceptions of the financial situation in Poland using different graphical tools for the heterogonous discrete longitudinal data sets and present demographics features for those changes. We will focus on the most important features of the categorical longitudinal data – category sequences and their graphical presentation. We aim to characterize the analyzed sequences on the basis of unidimensional indicators and composite complexity measures, as well as using mainly TraMineR [Gabadinho et al. 2017] package of R.
3
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Poczucie śląskości wśród Ślązaków – analiza empiryczna z wykorzystaniem modeli klas ukrytych

100%
Genge E.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2013
|
issue 4(42)
48-59
EN
The paper focuses on latent class models and their application for quantitative data. Latent class modeling is one of multivariate analysis techniques of the contingency table and can be viewed as a special case of model-based clustering, for multivariate discrete data. It is assumed that each observation comes from one of the numbers of subpopulations, with its own probability distribution. We used latent class analysis for grouping and detecting homogeneity of Silesian people using poLCA package of R. We analyzed data collected by the Department of Social Pedagogy, University of Silesia in Katowice.
4
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A comparison of dichotomous IRT models based on continuous and discrete latent trait – Polish households’ saving skills

100%
Genge E.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2017
|
issue 3 (57)
37-46
EN
Item response theory is considered to be one of the two trends in the methodological assessment of the reliability scale. Depending on the complexity of the adopted item parameterization, different types of IRT models for dichotomous items are defined. Most applications carried out in practice concern educational testing or psychological research and are based largely on the continuous assumption of the latent trait.The aim of this paper is to compare the estimation results of the discrete (formulated by the latent class approach) and continuous dichotomous IRT models in the analysis of Polish households’ saving skills as well as to assess Poles’ responses according to their ability to save money and the difficulty of the items (evaluation of the reliability of the item scale). All the computations and graphics in this paper are prepared using the MultiLCIRT and ltm packages of R.
5
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IRT and LC-IRT models for items with ordinal polytomous responses

100%
Genge E.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2017
|
issue 4 (58)
62-76
EN
Item response theory (IRT) is a model-based theory in which the responses to test items depend on some person and item characteristics, according to specific probabilistic rela-tions. The simplest and most popular are dichotomous IRT models that specify a single (i.e. unidimensional) latent trait under the assumption of normal distribution. This article reviews the latent class ordinal polytomous item response models (LC-IRT) and presents the compari-son with the well-known traditional IRT models (based on the assumption of a normally dis-tributed latent trait). The main goal of the article is to compare the estimation results of differ-ent kinds of ordinal polytomous IRT models with continuous and discrete latent variable in measuring job satisfaction in Poland. We analyzed data collected as part of the International Social Survey Programme using the ltm and MultiLCIRT packages of R.
6
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Rola kobiet w polskim społeczeństwie - analiza empiryczna z wykorzystaniem modeli klas ukrytych dla danych jakościowych

100%
Genge E.
Studia Ekonomiczne
|
2013
|
vol. 152
60-72
EN
The paper focuses on latent class models and it's application for quantitative data. Latent class modeling is one of a multivariate analysis techniques of the contingency table and can be viewed as a special case of model-based clustering, for multivariate discrete data. It is assumed that each observation comes from one of a number of subpopulations, with its own probability distribution. We used latent class analysis for grouping and detecting inhomogeneities of Polish opinions on role of women in polish society. We analyzed data collected as part of the Polish General Social Survey (GSS) using poLCA package of R.
7
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The multinomial mixture model - the analysis of students' attitude to the Silesia region

100%
Genge E.
Studia Ekonomiczne
|
2013
|
vol. 133
135-145
PL
Mieszanki rozkładów są stosowane wówczas, gdy zbiór obserwacji charakteryzuje się nadmiernym rozproszeniem. W literaturze najczęściej są spotykane mieszanki rozkładów normalnych (model-based clustering). W referacie zostaną przedstawione mieszanki rozkładów wielomianowych oraz wyniki ich zastosowań do podziału studentów o podobnych postawach wobec województwa śląskiego (jego tradycji, kultury, możliwości rozwoju itd.). Badania zostaną przeprowadzone za pomocą pakietu mixtools programu komputerowego R.
8
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Zastosowanie ukrytych modeli Markowa w analizie oszczędności wśród Polaków

100%
Genge E.
Studia Ekonomiczne
|
2014
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vol. 189
58-66
EN
In latent class analysis it is assumed that each observation comes from one of a number of classes (groups) and models each with its own probability distribution. When longitudinal data are to be analyzed, the research questions concern some form of change over time. Latent transition analysis (LTA) also known as latent Markov model, is a variation of the latent class model that is designed to model not only the prevalence of latent class membership, but the incidence of transitions over time in latent class membership. We used latent class analysis for grouping and detecting inhomogeneities of Polish attitude to saving money. We analyzed data collected as part of the Social Diagnosis, based on panel research using depmixS4 package of R.
9
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Czy łatwiej związać koniec z końcem? Badanie sytuacji materialnej gospodarstw domowych w Polsce z wykorzystaniem modeli panelowych

63%
Genge E., Trzęsiok J.
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
|
2017
|
issue 468
69-78
PL
Artykuł ma charakter aplikacyjny i porusza problem subiektywnej oceny sytuacji materialnej polskich gospodarstw domowych. Inspiracją do podjęcia tego tematu był raport z Diagnozy Społecznej 2015, w którym opublikowano wyniki badań sytuacji finansowej Polaków. W pracy wykorzystano zarówno analizę korespondencji, by zidentyfikować charakterystyki demograficzne towarzyszące różnym kategoriom subiektywnej oceny sytuacji finansowej polskich gospodarstw domowych, jak i wybrane modele panelowe, by określić dynamikę zmian tej sytuacji. Otrzymane wyniki pokazują, że stosunkowo najlepiej swoją sytuację materialną oceniają gospodarstwa pracowników i pracujących na własny rachunek, małżeństwa bez dzieci lub z jednym dzieckiem i mieszkańcy dużych miast. Wszystkie obliczenia i analizy wykonano za pomocą odpowiednich funkcji programu statystycznego R.
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