IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i22p2917-d680346.html
   My bibliography  Save this article

Stability of Dependencies of Contingent Subgroups with Merged Groups: Vaccination Case Study

Author

Listed:
  • Tomas Macak

    (Faculty of Economics and Management, Czech University of Life Sciences Prague, Kamycka 129, 16500 Prague, Czech Republic)

Abstract

The answers to extreme phenomena both in nature and in business sectors are the constructions of the distribution of random variables with extreme values. Another area in which appropriate theoretical research is conducted regarding the influence of suppressor (third) variables in categorical data. When examining dependencies in PivotTables, we often find it necessary to merge data into larger sets (e.g., due to a greater number of theoretical frequencies lower than their critical value). A phenomenon many exist wherein the partial relation is stronger than the zero relation. For example, in such a combination, instability may occur, which indicates contingent subgroups with the merged group. The dependence of dependencies is practically manifested because the data of contingent subgroups indicate inconsistent (inverted) conclusions compared to the associated group. For this reason, this paper aimed to find the critical ratios of partial probabilities in the contingency table of subgroups of the original variables, and to determine the conditions of result consistency and contingency stability, including the proof. For practical use and for the ease of repeating the proposed procedure, the solution is based on a case study that compares the effectiveness of vaccination.

Suggested Citation

  • Tomas Macak, 2021. "Stability of Dependencies of Contingent Subgroups with Merged Groups: Vaccination Case Study," Mathematics, MDPI, vol. 9(22), pages 1-12, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2917-:d:680346
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/22/2917/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/22/2917/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marks R. Nester, 1996. "An Applied Statistician's Creed," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(4), pages 401-410, December.
    2. Judea Pearl, 2014. "Comment: Understanding Simpson's Paradox," The American Statistician, Taylor & Francis Journals, vol. 68(1), pages 8-13, February.
    3. Margherita Carletti & Roberto Pancrazi, 2021. "Geographic Negative Correlation of Estimated Incidence between First and Second Waves of Coronavirus Disease 2019 (COVID-19) in Italy," Mathematics, MDPI, vol. 9(2), pages 1-9, January.
    4. Y. Ma, 2015. "Simpson’s paradox in GDP and per capita GDP growths," Empirical Economics, Springer, vol. 49(4), pages 1301-1315, December.
    5. Eubank, R.L. & Hsing, Tailen, 2008. "Canonical correlation for stochastic processes," Stochastic Processes and their Applications, Elsevier, vol. 118(9), pages 1634-1661, September.
    6. Gholamreza Hesamian, 2016. "One-way ANOVA based on interval information," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(11), pages 2682-2690, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shedrack Enyeribe Nwannunu & Sani Yahaya & Nurudeen Mohammed Moshud, 2023. "Improving Accounting and Finance-Students-Performance Through Group-Based Teaching and Learning: A Pedagogical Innovation," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(1), pages 950-963, January.
    2. Fort, Margherita & Ichino, Andrea & Rettore, Enrico & Zanella, Giulio, 2022. "Multi-cutoff RD designs with observations located at each cutoff: problems and solutions," CEPR Discussion Papers 16974, C.E.P.R. Discussion Papers.
    3. Fang Yin & Zhanli Sun & Liangzhi You & Daniel Müller, 2024. "Determinants of changes in harvested area and yields of major crops in China," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 16(2), pages 339-351, April.
    4. Ivan V. Savin, 2022. "Estimating the role of labor resources reallocation between sectors on the growth of aggregate labor productivity in the Russian economy," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 8(1), pages 57-67.
    5. Robert T. Krafty, 2016. "Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 435-450, July.
    6. King, David, 2010. "A note on the cross-covariance operator and on congruence relations for Hilbert space valued stochastic processes," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 361-365, March.
    7. Tian, Songtao & Liu, Zhirong, 2020. "Emergence of income inequality: Origin, distribution and possible policies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    8. Ruzong Fan & Hong-Bin Fang, 2022. "Stochastic functional linear models and Malliavin calculus," Computational Statistics, Springer, vol. 37(2), pages 591-611, April.
    9. Ulrich Daepp & Pamela Gorkin & Karl Voss, 2017. "Quiz 1: What Color Was George Washington’s White Horse? The Mathematical Version," The Mathematical Intelligencer, Springer, vol. 39(4), pages 9-17, December.
    10. Swamy, P.A.V.B. & Mehta, J.S. & Tavlas, G.S. & Hall, S.G., 2015. "Two applications of the random coefficient procedure: Correcting for misspecifications in a small area level model and resolving Simpson's paradox," Economic Modelling, Elsevier, vol. 45(C), pages 93-98.
    11. David E. Bloom & Mathew McKenna & Klaus Prettner, 2018. "Demography, Unemployment, Automation, and Digitalization: Implications for the Creation of (Decent) Jobs, 2010–2030," NBER Working Papers 24835, National Bureau of Economic Research, Inc.
    12. Judea Pearl, 2017. "Detecting Latent Heterogeneity," Sociological Methods & Research, , vol. 46(3), pages 370-389, August.
    13. Andrew Briggs & Richard Nixon & Simon Dixon & Simon Thompson, 2005. "Parametric modelling of cost data: some simulation evidence," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 421-428, April.
    14. Norman Fickel, 2001. "Sequential Regression: A Neodescriptive Approach to Multicollinearity," EERI Research Paper Series EERI_RP_2001_09, Economics and Econometrics Research Institute (EERI), Brussels.
    15. Aris Spanos, 2021. "Yule–Simpson’s paradox: the probabilistic versus the empirical conundrum," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 605-635, June.
    16. Cho, Haeran & Goude, Yannig & Brossat, Xavier & Yao, Qiwei, 2013. "Modeling and forecasting daily electricity load curves: a hybrid approach," LSE Research Online Documents on Economics 49634, London School of Economics and Political Science, LSE Library.
    17. Daniel Możdżyński & Wojciech Cellary, 2022. "Determinants of the Acceptance of Mobile Payment Systems by E-Merchants," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 20(1), pages 1-23, January.
    18. Love, Peter E.D. & Ahiaga-Dagbui, Dominic D. & Irani, Zahir, 2016. "Cost overruns in transportation infrastructure projects: Sowing the seeds for a probabilistic theory of causation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 184-194.
    19. Johannesson, Louise, 2016. "Supporting Developing Countries in WTO Dispute Settlement," Working Paper Series 1120, Research Institute of Industrial Economics.
    20. Kristoffer Rørstad & Dag W Aksnes & Fredrik Niclas Piro, 2021. "Generational differences in international research collaboration: A bibliometric study of Norwegian University staff," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-21, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2917-:d:680346. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.