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1

Porównanie modeli regresji logistycznej odpornych na problem całkowitego rozdzielenia

100%
Fijorek K.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
|
2012
|
issue 884
143-156
EN
Applying logistic regression to small-sized data sets very often leads to the problem of complete separation. Generally speaking, separation is caused by a linear combination of covariates that perfectly separates successes (events) from failures (non-events). In such cases, results obtained by maximum likelihood method should not be trusted, since at least one parameter estimate diverges to infinity. A systematic review of the literature resulted in two theoretically sound procedures which always arrive at finite estimates, i.e. those of H. Heinze and S. Schemper (2002) and also R. Rousseeuw and C. Christmann (2003). The main goal of the paper is to compare them.
2
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Analiza problemów finansowych gospodarstw domowych w Polsce z zastosowaniem regresji logistycznej

80%
Gołaś Z., Anioła P.
Journal of Agribusiness and Rural Development
|
2012
|
issue 1(23)
25-35
EN
This article attempted to identify the socio-economic and demographic factors influencing the problems with arrears in Polish households. The micro data from Social Diagnosis were used. In order to achieve the main goal the logistic regression analysis was used.
3

DETERMINANTS OF ECONOMIC INACTIVITY AMONG THE DISABLED IN POLAND (Determinanty biernosci zawodowej osob niepelnosprawnych w Polsce)

80%
Bieszk-Stolorz B.
Optimum. Studia Ekonomiczne
|
2012
|
issue 1(55)
143-153
EN
In Poland, disabled people most frequently remain part of the unused labour force. Despite the fact that in recent years the number of disabled Poles who found employment has risen, their employment rate is still rather low. The majority of them (83% in 2010) are absent from the job market. The aim of the paper is to investigate how gender, place of residence, education, age and level of disability affect the economic inactivity of the disabled and what impact their gender, place of residence and level of disability have on the likelihood of the reason for the inactivity. The author used the Polish Central Statistical Office data concerning the 4th quarter of 2010. The data were analysed by means of the logistic regression model for the dependent dichotomous variable, as well as by means of the multinomial logistic regression model. The assessed parameters helped to determine the inactivity risk quotient in relation to economic activity. They also permitted to calculate the probability of the disabled people's economic inactivity due to a particular reason.
4
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Choosing Among Discrete Choice Models for Voting Behavior

80%
Dubrow J. K.
ASK. Research and Methods
|
2007
|
vol. 16
9-23
EN
Analyses presented in this paper aim at testing demographic cues hypothesis, which explains voting behavior as a function of the distance between the voter and the object of the vote, expressed as demographic similarity. Four types of multivariate regression models - binomial logistic (BNL), multinomial logistic (MNL), contrast logistic (CON­TRAST), and conditional logistic (CLOGIT) - are applied to explain vote choice among Polish parties in the 1997 parliamentary election. For all models the author uses survey data combined with information on political parties derived from characteristics of the electoral candidates. The results demonstrate that for testing demographic cues hypothesis CLOGIT and BNL are the most advisable options in terms of elucidation of the regression coefficients; MNL and CONTRAST involve cumbersome interpretation and their fit to the theory is questionable.
5
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Kontrasty v logistické regresi

70%
Rehakova B.
Sociologický časopis. Czech Sociological Review
|
2008
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vol. 44
|
issue 4
745-766
EN
The article deals with the use of various types of contrasts, especially in logistic regression. Contrasts were originally developed within the framework of the analysis of variance. They gradually expanded into other statistical methods, for example, into logistic regression and loglinear or logit models. They are also used in linear regression when there are categorical variables among the explaining variables. Contrasts represent a method for working with variables that are not numerical but categorical. The article refers to the well-known types, such as indicator, simple, deviation, repeated, Helmert, difference and polynomial contrasts. Several others are also proposed. Contrasts are classified according to the appropriateness of their use for different types of categorical variables (nominal, ordinal). Their meaning and effect on the interpretation of odds ratios are explained on the basis of examples created using real data.
6

DETERMINANTS OF INDIVIDUAL LIFE-RELATED INSURANCE CONSUMPTION: THE CASE OF THE SLOVAK REPUBLIC

70%
Ondruška T.
Ekonomický časopis (Journal of Economics)
|
2020
|
vol. 68
|
issue 8
846 – 863
EN
The premature death of a breadwinner, serious injuries or an insufficient level of income during retirement can decrease the living standard of households substantially. Life insurance represents a tool for managing such kinds of uncertainties. However, individuals do not adequately consider this need for security. Papers focusing on factors determining life-related insurance consumption identified many variations in the effect of these factors. The reasons are not clear, but one of the explanations is the aggregated nature of life insurance without focus on the type of covered risks. Based on survey data, we confirm the differences in the determinants of various risks covered by life insurance. In the general life insurance model, we confirmed the following as significant determinants: gender, head of household status, combination of marital status and dependent children, saving behaviour and employment status. In the private pension insurance coverage, significant determinants are age, education, saving behaviour and employment status. The willingness to buy accident cover with life insurance is determined by the saving behaviour and employment status. Marginal effect has the status of head of household.
7

DOES RENT DEREGULATION INFLUENCE HOUSING TENURE CHOICE? THE CASE OF THE CZECH REPUBLIC

61%
Špalková D., Špalek J.
Ekonomický časopis (Journal of Economics)
|
2014
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vol. 62
|
issue 7
692 – 708
EN
The choice between buying and renting house is usually referred to as tenure choice. Existing literature defines several typical factors (patterns) which influence this key decision every household has to make. In our analysis we propose one more factor which might be of interest. Based on the data covering last phase of the rent deregulation process in the Czech Republic (CR) in 2005 – 2011 we assess to what extent rent deregulation in the CR has influenced the tenure choice patterns. Our analysis using logit model did prove that regulated rents were an important factor affecting tenure choice. After deregulation households living in apartments with regulated rent preferred to buy house rather than stay in rental sector. The results show that also in the CR was tenure choice influenced by household income, education, marital status. By contrast, gender, age, number of children or retired persons in the household turned out to be insignificant.
8

CORPORATE BANKRUPTCY PREDICTION: EVIDENCE FROM WHOLESALE COMPANIES IN THE WESTERN EUROPEAN COUNTRIES

61%
Vuković B., Milutinović S., Milićević N., Jakšić D.
Ekonomický časopis (Journal of Economics)
|
2020
|
vol. 68
|
issue 5
477 – 498
EN
The aim of this paper was to develop a model that can forecast the bankruptcy of the companies using logistic regression model. The sample consists of 23 bankrupts and 30 healthy companies selected from the initial sample of all large active companies (1740 companies). The companies operate in the trade industry, sector wholesale in Western Europe, in the time period from 2010 to 2018. The logit model was based on the choice between 23 financial indicators. The obtained results with high accuracy showed that the most important bankruptcy predictors were the following five indicators: return on equity, current assets/ total assets, solvency, working capital turnover, stocks/current assets. The developed model provides an opportunity for all external stakeholders to easily identify companies that are facing the risk of bankruptcy. The possibility of the company’s bankruptcy prediction, the assessment of risk and threatened circumstances to continue business is crucial information for making all future business decisions with the company.
9

Zastosowanie regresji logistycznej w badaniach eksperymentalnych

61%
Danieluk B.
Psychologia Społeczna
|
2010
|
vol. 5
|
issue 2-3(14)
199-216
EN
In experimental practice we offten face the situation where the measured dependent variable takes one of two values only: 0 - lack of the measured characteristic or 1 - observation of the measured characteristic (behavior, consent to something, displaying an attitude or an opinion etc.). Both the general linear model as well as the linear regression analysis cannot be applied to dichotomous, nominal dependent variables. In such cases we are forced to use the non-linear analysis. Logistic regression is the model used for this type of dependent variables. This article presents application of the binomial logistic regression in experimental research. It explains specification and interpretation of typical logistic regression coefficients such as odds ratio, Wald coefficients, likelihood ratios. It presents the estimation procedure of the model parameters with maximum likelihood procedure and the Hosmer-Lemeshow goodness of fit test. Introduced were simple sample analyses (with nominal and quantitative predictors), a two-factor analysis as well as a two-factor analysis with interaction effect. The number of formulas and algebraic transformations were cut to the necessary minimum and the shown sample analysis and their interpretation were conducted step by step with the SPSS Statistics Pack version 17.0 PL.
10

LOCATION FACTORS OF NON-PUBLIC HIGHER EDUCATIONAL INSTITUTIONS: THE EVIDENCE FROM POLAND

61%
Bajerski A.
Ekonomický časopis (Journal of Economics)
|
2011
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vol. 59
|
issue 2
115 – 131
EN
The aim of the article is to find out the location factors of non-public higher education institutions in Poland after 1989. The logistic regression was used to meet this goal. Five sets of variables were selected for the initial stage of analysis. These were: population of the town and its hinterland, distance to the nearest academic centre, education level of inhabitants, local authority revenue and the existence nearby of other, potentially competing colleges. The analysis proved that the most important location factor of non-public higher education institutions was the existence of other, potentially competing colleges in the vicinity. This means that in the development of the network of non-public higher education institutions in Poland a key role was played by the „filling” of spatial niches on the education market.
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