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Krzywe operacyjno-charakterystyczne w ewaluacyjnych badaniach marketingowych

100%
Sagan A.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
|
2011
|
issue 864
5-17
EN
The articles examines the characteristics and use of the receiver operator characteristic (ROC) in research on marketing phenomena. This approach is an extremely popular tool for assessing prediction accuracy in medical research and signal detection, and is being ever more widely used in social and marketing research. The article presents the main indicators of classification accuracy for contingency tables (2×2) and the principles governing the use of ROC curves. The use of these curves is illustrated with an analysis of the accuracy of the choice of car (new or used) based on the structure of customer benefits.
2
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ON THE METHOD OF COMPARING STRUCTURES BASED ON THE DATA IN THE CONTINGENCY TABLES

100%
Polko D.
Acta Universitatis Lodziensis. Folia Oeconomica
|
2014
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vol. 3
|
issue 302
EN
Comparison of populations is one of the most important problems in statistics. The most common comparisons apply to two populations, but comparisons of k populations, where k > 2 are also carried out. Parametric methods allow to compare the means, variances or proportions. The non-parametric methods allow to compare the distributions of two or more populations. The problem of comparison structures based on data in contingency tables is analyzed in the paper. The permutation tests were applied in the multivariate nominal data structure comparison.
3
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Comparison of methods used for filling partially unobserved contingency tables

100%
Kot M., Kamiński B.
Przegląd Statystyczny
|
2021
|
vol. 68
|
issue 4
1-20
EN
In this article, we investigate contingency tables where the entries containing small counts are unknown for data privacy reasons. We propose and test two competitive methods for estimating the unknown entries: our modification of the Iterative Proportional Fitting Procedure (IPFP), and one of the Monte Carlo Markov Chain methods called Shake-and-Bake. We use simulation experiments to test these methods in terms of time complexity and the accuracy of searching the space of feasible solutions. To simplify the estimation procedure, we propose to pre-process partially unknown contingency tables with simple heuristics and dimensionality-reduction techniques to find and fill all trivial entries. Our results demonstrate that if the number of missing cells is not very large, the pre-processing is often enough to find fillings for the unknown values in contingency tables. In the cases where simple heuristics are insufficient, the Shake-and-Bake technique outperforms the modified IPFP in terms of time complexity and the accuracy of searching the space of feasible solutions.
4

The Problem of Zero Cells in the Analysis of Contingency Tables

63%
Brzezińska J.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
|
2015
|
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
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