IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i21p2797-d672364.html
   My bibliography  Save this article

Proposal of the Dichotomous STATIS DUAL Method: Software and Application for the Analysis of Dichotomous Data, Applied to the Test of Learning Styles in University Students

Author

Listed:
  • Victoria I. Ballesteros-Espinoza

    (Departamento de Estadística, Facultad de Medicina, Universidad de Salamanca, Campus Miguel de Unamuno, Calle Alfonso X El Sabio, s/n, 37007 Salamanca, Spain
    Centro de Investigación de Estadística Multivariante Aplicada (CIEMA), Universidad de Colima, Ignacio Zaragoza 64, Colima 28000, Mexico)

  • Miguel Rodríguez-Rosa

    (Departamento de Estadística, Facultad de Medicina, Universidad de Salamanca, Campus Miguel de Unamuno, Calle Alfonso X El Sabio, s/n, 37007 Salamanca, Spain)

  • Ana B. Sánchez-García

    (Institute for Community Inclusion (INICO), University of Salamanca, 37005 Salamanca, Spain)

  • Purificación Vicente-Galindo

    (Departamento de Estadística, Facultad de Medicina, Universidad de Salamanca, Campus Miguel de Unamuno, Calle Alfonso X El Sabio, s/n, 37007 Salamanca, Spain)

Abstract

The present work analyzed a review of methods for analyzing sequences of matrices or dichotomous data. A new method for a sequence of dichotomous matrices with a different number of rows is presented; the Dichotomous STATIS DUAL. Suppose we match the sequence of matrices by different years, with this method. In that case, we can graphically represent the relations among the different columns of all the matrices, and the relations between those columns and the different years, because everything can be represented in the same plots. As in all STATIS methods, three different plots can get: (i) the interstructure, with the relations among the years; (ii) the compromise, with the stable part of the relations between the columns; and (iii) the intrastructure (also known as trajectories), with the relations between columns and years, in other words, the evolution of the columns through the time. This new mathematical method can be used with all kinds of dichotomous data, thanks to the software we propose. In the present work, the software was applied to the assessment of learning styles.

Suggested Citation

  • Victoria I. Ballesteros-Espinoza & Miguel Rodríguez-Rosa & Ana B. Sánchez-García & Purificación Vicente-Galindo, 2021. "Proposal of the Dichotomous STATIS DUAL Method: Software and Application for the Analysis of Dichotomous Data, Applied to the Test of Learning Styles in University Students," Mathematics, MDPI, vol. 9(21), pages 1-14, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:21:p:2797-:d:672364
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/21/2797/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/21/2797/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. P. Robert & Y. Escoufier, 1976. "A Unifying Tool for Linear Multivariate Statistical Methods: The RV‐Coefficient," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 25(3), pages 257-265, November.
    2. Vallejo-Arboleda, Amparo & Vicente-Villardon, Jose L. & Galindo-Villardon, M.P., 2007. "Canonical STATIS: Biplot analysis of multi-table group structured data based on STATIS-ACT methodology," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4193-4205, May.
    3. Jacques Bénasséni & Mohammed Bennani Dosse, 2012. "Analyzing multiset data by the Power STATIS-ACT method," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(1), pages 49-65, April.
    4. Vivien, Myrtille & Sabatier, Robert, 2004. "A generalization of STATIS-ACT strategy: DO-ACT for two multiblocks tables," Computational Statistics & Data Analysis, Elsevier, vol. 46(1), pages 155-171, May.
    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. Mariela González-Narváez & María José Fernández-Gómez & Susana Mendes & José-Luis Molina & Omar Ruiz-Barzola & Purificación Galindo-Villardón, 2021. "Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    2. Isabel Gallego-Álvarez & Miguel Rodríguez-Rosa & Purificación Vicente-Galindo, 2021. "Are Worldwide Governance Indicators Stable or Do They Change over Time? A Comparative Study Using Multivariate Analysis," Mathematics, MDPI, vol. 9(24), pages 1-19, December.
    3. Carmen C. Rodríguez-Martínez & Isabel María García-Sánchez & Purificación Vicente-Galindo & Purificación Galindo-Villardón, 2019. "Exploring Relationships between Environmental Performance, E-Government and Corruption: A Multivariate Perspective," Sustainability, MDPI, vol. 11(22), pages 1-16, November.
    4. Cling, Jean-Pierre & Delecourt, Clément, 2022. "Interlinkages between the Sustainable Development Goals," World Development Perspectives, Elsevier, vol. 25(C).
    5. Delimiro Visbal-Cadavid & Mónica Martínez-Gómez & Rolando Escorcia-Caballero, 2020. "Exploring University Performance through Multiple Factor Analysis: A Case Study," Sustainability, MDPI, vol. 12(3), pages 1-24, January.
    6. Florence Jacquet & A Aboul-Naga & Bernard Hubert, 2020. "The contribution of ARIMNet to address livestock systems resilience in the Mediterranean region," Post-Print hal-03625860, HAL.
    7. Rauf Ahmad, M., 2019. "A significance test of the RV coefficient in high dimensions," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 116-130.
    8. Grothe, Oliver & Schnieders, Julius & Segers, Johan, 2013. "Measuring Association and Dependence Between Random Vectors," LIDAM Discussion Papers ISBA 2013026, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Roberta De Vito & Ruggero Bellio & Lorenzo Trippa & Giovanni Parmigiani, 2019. "Multi‐study factor analysis," Biometrics, The International Biometric Society, vol. 75(1), pages 337-346, March.
    10. Carmen C. Rodríguez-Martínez & Mitzi Cubilla-Montilla & Purificación Vicente-Galindo & Purificación Galindo-Villardón, 2023. "X-STATIS: A Multivariate Approach to Characterize the Evolution of E-Participation, from a Global Perspective," Mathematics, MDPI, vol. 11(6), pages 1-15, March.
    11. Dorota Toczydlowska & Gareth W. Peters, 2018. "Financial Big Data Solutions for State Space Panel Regression in Interest Rate Dynamics," Econometrics, MDPI, vol. 6(3), pages 1-45, July.
    12. Reza Salimi & Kamran Pakizeh, 2024. "The extension of Pearson correlation coefficient, measuring noise, and selecting features," Papers 2402.00543, arXiv.org.
    13. Haouès-Jouve Sinda & Lemonsu Aude & Gauvrau Benoit & Amossé Alexandre & Can Arnaud & Carrissimo Bertrand & Gaudio Noémie & Hidalgo Julia & Lopez-Rieu Claudia & Chouillou Delphine & Richard Isabelle, 2022. "Cross-analysis for the assessment of urban environmental quality: An interdisciplinary and participative approach," Environment and Planning B, , vol. 49(3), pages 1024-1047, March.
    14. Oliveira, Manuela M. & Mexia, Joao T., 2007. "Modelling series of studies with a common structure," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5876-5885, August.
    15. Górecki Tomasz & Krzyśko Mirosław & Ratajczak Waldemar & Wołyński Waldemar, 2016. "An Extension of the Classical Distance Correlation Coefficient for Multivariate Functional Data with Applications," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 449-466, September.
    16. Jean-Pierre Rossi & Maxime Nardin & Martin Godefroid & Manuela Ruiz-Diaz & Anne-Sophie Sergent & Alejandro Martinez-Meier & Luc Pâques & Philippe Rozenberg, 2014. "Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-13, September.
    17. Mordant, Gilles & Segers, Johan, 2022. "Measuring dependence between random vectors via optimal transport," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    18. Papageorgiou, Ioulia & Moustaki, Irini, 2019. "Sampling of pairs in pairwise likelihood estimation for latent variable models with categorical observed variables," LSE Research Online Documents on Economics 87592, London School of Economics and Political Science, LSE Library.
    19. Sneha Vishwanath & Alexandre G de Brevern & Narayanaswamy Srinivasan, 2018. "Same but not alike: Structure, flexibility and energetics of domains in multi-domain proteins are influenced by the presence of other domains," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-26, February.
    20. A. Iodice D’Enza & A. Markos & F. Palumbo, 2022. "Chunk-wise regularised PCA-based imputation of missing data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 365-386, June.

    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:21:p:2797-:d:672364. 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.