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1

A Multivariate Statistical Analysis of the Information Society in Poland

100%
Brzezińska J.
Argumenta Oeconomica Cracoviensia
|
2018
|
issue 19
83-101
EN
Widespread access to high-speed Internet, user-friendly public e-services and the increasing digital competence of society are the main goals for the coming years according to the latest reports published by the Central Statistical Office in Poland. These goals are included in the Operational Programme Digital Poland. This technological development is also connected with the development of economic areas and public services. The rapidly increasing significance of information and electronic services, and thus the application of information and communication technologies (ICT) in the economy, public administration (central and local), and in the everyday life of citizens has triggered a new transformation trend – a transformation towards the information society. This term describes a society for which the processing of information with the use of ICT solutions creates significant economic, social and cultural value. In this paper we present the current state, main aspects, vision and mission of the information society in Poland and carry out a statistical analysis of the information society in Poland using multivariate statistical methods. All the calculations are based on data from the Central Statistical Office and they are conducted using R software.
PL
Powszechny dostęp do szybkiego internetu, przyjazne dla użytkownika e-usługi publiczne i rosnące kompetencje cyfrowe społeczeństwa są głównymi celami na najbliższe lata według najnowszych raportów opublikowanych przez Główny Urząd Statystyczny w Polsce. Cele te zawarte są w Programie Operacyjnym Polska Cyfrowa. Rozwój technologiczny wiąże się również z rozwojem obszarów gospodarczych i usług publicznych. Szybko rosnące znaczenie informacji i elektroniki usług, a tym samym zastosowania technologii informacyjnych i komunikacyjnych (Information and Communication Technologies – ICT) w gospodarce, administracji publicznej (centralnej i lokalnej), a także w codziennym życiu obywateli spowodowało nowy trend transformacji – transformację w kierunku społeczeństwa informacyjnego. Termin ten opisuje społeczeństwo, dla którego przetwarzane informacje z wykorzystaniem rozwiązań ICT stwarzają istotną ekonomiczną, społeczną oraz kulturową wartość. W artykule przedstawiono obecny stan, główne aspekty oraz wizję i misję społeczeństwa informacyjnego w Polsce. Przeprowadzono statystyczną analizę społeczeństwa informacyjnego w Polsce za pomocą wielowymiarowych metod statystycznych. Wszystkie obliczenia oparto na danych pochodzących z Głównego Urzędu Statystycznego i wykonano z wykorzystaniem programu R.
2

The Problem of Zero Cells in the Analysis of Contingency Tables

100%
Brzezińska J.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
|
2015
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issue 5(941)
49-61
EN
Log-linear analysis is a statistical tool used to analyse the independence of categorical data in contingency tables. With this method, any number of nominal or ordinal variables can be analysed: interactions can be included in the model, various types of association can be analysed, and the analysis provides a formal model equation. Although log-linear analysis is a versatile statistical method, there are some limitations in using it due to zero cells. Zero cells in contingency table are of two types: fixed (structural) and sampling zeros. Fixed zeros occur when it is impossible to observe values for certain combinations of the variable. Sampling zeros are due to sampling variations and the relatively small size of the sample when compared with a large number of cells. In the paper several options will be presented for how to deal with zero cells in a table. All calculations will be conducted in R
PL
Analiza logarytmiczno-liniowa jest metodą badania zależności pomiędzy zmiennymi niemetrycznymi w tablicy kontyngencji, która pozwala analizować dowolną liczbę zmiennych nominalnych i porządkowych. Pomimo że jest ona uniwersalną metodą analizy zmiennych niemetrycznych, występują jednak pewne ograniczenia w jej stosowaniu ze względu na zerowe liczebności. Zera występujące w tablicy mogą być dwojakiego rodzaju: strukturalne lub związane ze schematem losowania. Zera strukturalne pojawiają się wtedy, gdy nie jest możliwa obserwacja kategorii zmiennej, a zera związane ze schematem losowania występują w małych próbach i znikają, gdy próba zostanie odpowiednio zwiększona. W artykule zaprezentowano sposoby radzenia sobie z zerowymi liczebnościami w tablicy kontyngencji. Wszystkie obliczenia przeprowadzono w programie R
3
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Latent class analysis in the evaluation of items in survey research

100%
Brzezińska J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2018
|
issue vol. 22 no. 3
55-65
EN
Latent class analysis has been widely used in the measurement models. Models based on latent variables have a wide range of applications in the presence of repeated ob-servations, longitudinal data, and multilevel data. In this paper we present and apply log-linear analysis as a method for the analysis of multi-way tables. We also present a latent variable model based on a variable that is not directly observed. The basic model postulates an underlying categorical latent variable; within any category of the latent variable the manifest or observed categorical variables are assumed independent of one another (axiom of conditional independence). In this paper we present the results of a survey research based on categorical data and the author`s questionnaire. We present the results of the latent class analysis in the classification of respondents into clusters characterized by similar attitudes and features in economic research. We also conduct a prior log-linear analysis for a multi-way contingency table. All the calculations are conducted in R.
4
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Visual techniques for categorical data in R

100%
Brzezińska J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2017
|
issue 3 (57)
26-36
EN
Visualization is one of the most important parts of statistical analysis. In this paper we present a new method of multiple bar charts to display the frequencies of data tables split up into conditional relative frequencies of one target variable and the absolute frequencies of the corresponding combinations of the remaining explanatory variables. In this paper we present the R package extracat allowing for new graphical tools: rmp and cpcp plot [Pilhoefer, Unwin 2013]. The first plot uses the a crossover of mosaicplots and multiple barcharts to display the frequencies of a contingency table split up into conditional relative frequencies of one target variable and the absolute frequencies of the corresponding combination of the remaining explanatory variables. It provides a well-structured representation of the data with the possibility of easy interpretation. Another plot presented in the paper is the cpcp plot using parallel coordinates. Sequences of points are used to represent each of the variable categories, while ordering algorithms are applied to represent a hierarchical structure in the dataset.
5
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Item response theory models in the measurement theory with the use of LTM package in R

100%
Brzezińska J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2018
|
issue vol. 22 no. 1
11-25
EN
Item Response Theory (IRT) is an extension of the Classical Test Theory (CCT) and focuses on how specific test items function in assessing a construct. They are widely known in psychology, medicine, and marketing, as well as in social sciences. An item response model specifies a relationship between the observable examinee test performance and the unobservable traits or abilities assumed to underlie performance on the test. Within the broad framework of item response theory, many models can be operationalized because of the large number of choices available for the mathematical form of the item characteristic curves. In this paper we introduce several types of IRT models such as: the Rasch, and the Birnbaum model. We present the main assumptions for IRT analysis, estimation method, properties, and model selection methods. In this paper we present the application of IRT analysis for binary data with the use of the ltm package in R.
6
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Statistical analysis of economic poverty in Poland using R

100%
Brzezińska J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2018
|
issue vol. 22 no. 2
45-53
EN
Economic poverty is one of the more common and complex problems in the modern world, as well as in Poland. This is a complex and multidimensional phenomenon, and therefore there is no single universally valid definition of poverty. This article presents a statistical analysis of economic poverty in Poland based on real data from the Central Statistical Office of Poland. An in-depth statistical analysis of the social situation of Poles will be presented, as well as an attempt to examine interdependencies in the occurrence of various forms of poverty and social exclusion in Poland. In the article, several multivariate statistical methods are presented together with the graphical presentation of results. We present a correspondence analysis with a perception map, as well as the advanced modern visualizing tool for categorical data. All the calculations were conducted using R software.
7
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Visualization of categorical data using extracat package in R

100%
Brzezińska J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2018
|
issue vol. 22 no. 2
9-19
EN
Visualization in research process plays a crucial role. There are several advanced plots for visualizing categorical data, such as mosaic, association, double-decker, sieve or fourfold plot that are based on the graphical presentation of residuals in a contingency table. In this paper we present new methods for visualizing categorical data such as rmb, fluctile and scpcp plot available in extracat package in R. This package provides a well-structured representation of categorical data and allows for a detailed presentation of the relationship between categories in terms of proportions. We describe rmb, fluctile and cpcp. Those plots are based on the concept of multiple bar charts, a fluctuation diagram from a multidimensional table and parallel coordinates respectively. Such plots are mostly used for a visualization of a contingency table or a data frame; they can also be used for exploratory analysis and allows for a graphical presentation even for a high number of variables [Pilhöfer, Unwin 2013]. All the calculations and plots are obtained using R software.
8
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Modelowe metody analizy danych wielowymiarowych tablic kontyngencji w badaniach opinii publicznej

100%
Brzezińska J.
Studia Ekonomiczne
|
2014
|
vol. 195
11-20
EN
The methods for analyzing cross-classified tables are usually to test relations between two variables taken one pair at a time. Further development of those methods allowed to move from two dimensional tables to high dimensional tables, where dimensionality of a cross-table refers to the number of variables. It allowed to transform nonmodel- based to model-based methods providing the equation of a mathematical model, the use of estimation method and variety of visualizing tools. This paper describes how complex qualitative data may be described by a mathematical model. One of the method presented is log-linear analysis.
9
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IRT-based conjoint analysis in the optimization of banking products

51%
Sagan A., Rybicka A., Brzezińska J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2017
|
issue 3 (57)
47-58
EN
Conjoint measurement and analysis have a common underlying psychometric and statistical assumption concerning axioms of additivity and two-way frame of reference in preference measurement. However, whereas the former concept is widely used in the fundamental measurement of subject × object dominance structures as in IRT and Rasch measurement models, the latter is utilized in a broad family of object × object dominance structures in both compositional (i.e. Thurstone case III and V) as well as decompositional (classical conjoint experiments and BTL/alpha simulation) preference measurement models. These two traditions are rarely combined in one measurement model and research design that integrates subject × object × object measurement [Neubauer 2003]. The aim of the paper is to adopt and compare three types of preference measurement models in the area of banking products in Poland: 1. paired-comparisons and rating scale conjoint experiment, 2. IRT-based conjoint (Rasch and Birnbaum politomous models), 3. compositional Thurstone III/V models [Bockenholt 2006]. Part-worth utilities are used for product optimization and comparison across the estimated models.
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