IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0071940.html
   My bibliography  Save this article

The Use of Bayesian Latent Class Cluster Models to Classify Patterns of Cognitive Performance in Healthy Ageing

Author

Listed:
  • Patrício Soares Costa
  • Nadine Correia Santos
  • Pedro Cunha
  • Joana Almeida Palha
  • Nuno Sousa

Abstract

The main focus of this study is to illustrate the applicability of latent class analysis in the assessment of cognitive performance profiles during ageing. Principal component analysis (PCA) was used to detect main cognitive dimensions (based on the neurocognitive test variables) and Bayesian latent class analysis (LCA) models (without constraints) were used to explore patterns of cognitive performance among community-dwelling older individuals. Gender, age and number of school years were explored as variables. Three cognitive dimensions were identified: general cognition (MMSE), memory (MEM) and executive (EXEC) function. Based on these, three latent classes of cognitive performance profiles (LC1 to LC3) were identified among the older adults. These classes corresponded to stronger to weaker performance patterns (LC1>LC2>LC3) across all dimensions; each latent class denoted the same hierarchy in the proportion of males, age and number of school years. Bayesian LCA provided a powerful tool to explore cognitive typologies among healthy cognitive agers.

Suggested Citation

  • Patrício Soares Costa & Nadine Correia Santos & Pedro Cunha & Joana Almeida Palha & Nuno Sousa, 2013. "The Use of Bayesian Latent Class Cluster Models to Classify Patterns of Cognitive Performance in Healthy Ageing," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    • Handle: RePEc:plo:pone00:0071940
    DOI: 10.1371/journal.pone.0071940
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0071940
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0071940&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0071940?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Anton K. Formann, 2003. "Latent Class Model Diagnosis from a Frequentist Point of View," Biometrics, The International Biometric Society, vol. 59(1), pages 189-196, March.
    2. Chung H. & Loken E. & Schafer J.L., 2004. "Difficulties in Drawing Inferences With Finite-Mixture Models: A Simple Example With a Simple Solution," The American Statistician, American Statistical Association, vol. 58, pages 152-158, May.
    3. Haughton, Dominique & Legrand, Pascal & Woolford, Sam, 2009. "Review of Three Latent Class Cluster Analysis Packages: Latent Gold, poLCA, and MCLUST," The American Statistician, American Statistical Association, vol. 63(1), pages 81-91.
    4. Ana Cristina Paulo & Adriana Sampaio & Nadine Correia Santos & Patrício Soares Costa & Pedro Cunha & Joseph Zihl & João Cerqueira & Joana Almeida Palha & Nuno Sousa, 2011. "Patterns of Cognitive Performance in Healthy Ageing in Northern Portugal: A Cross-Sectional Analysis," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-9, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Morteza Nagahi & Niamat Ullah Ibne Hossain & Raed Jaradat & Vidanelage Dayarathna & Chuck Keating & Simon Goerger & Michael Hamilton, 2022. "Classification of individual managers' systems thinking skills based on different organizational ownership structures," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(2), pages 258-273, March.

    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. Cristina Bosch-Farré & Josep Garre-Olmo & Anna Bonmatí-Tomàs & Maria Carme Malagón-Aguilera & Sandra Gelabert-Vilella & Concepció Fuentes-Pumarola & Dolors Juvinyà-Canal, 2018. "Prevalence and related factors of Active and Healthy Ageing in Europe according to two models: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE)," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-19, October.
    2. Shaosheng Jin & Bashiru Mansaray & Xin Jin & Haoyang Li, 2020. "Farmers’ preferences for attributes of rice varieties in Sierra Leone," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(5), pages 1185-1197, October.
    3. Bart Neuts & João Romão & Peter Nijkamp & Asami Shikida, 2016. "Market segmentation and their potential economic impacts in an ecotourism destination," Tourism Economics, , vol. 22(4), pages 793-808, August.
    4. Solomon Zena Walelign & Mariève Pouliot & Helle Overgaard Larsen & Carsten Smith-Hall, 2015. "A novel approach to dynamic livelihood clustering: Empirical evidence from Nepal," IFRO Working Paper 2015/09, University of Copenhagen, Department of Food and Resource Economics.
    5. Shimshock, Stephen & Chor, Ka Ho Brian & Brylske, Paul D., 2022. "Using latent class analysis to identify clinical subgroups and pathways of youth in a therapeutic foster care program," Children and Youth Services Review, Elsevier, vol. 141(C).
    6. Xiang, Qinfang & Edwards, Jode & Gadbury, Gary L., 2006. "Interval estimation in a finite mixture model: Modeling P-values in multiple testing applications," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 570-586, November.
    7. Marijn A. Weele & Frank J. Rijnsoever & Menno Groen & Ellen H. M. Moors, 2020. "Gimme shelter? Heterogeneous preferences for tangible and intangible resources when choosing an incubator," The Journal of Technology Transfer, Springer, vol. 45(4), pages 984-1015, August.
    8. Formann, Anton K., 2007. "Mixture analysis of multivariate categorical data with covariates and missing entries," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5236-5246, July.
    9. van Rijnsoever, Frank J. & Kempkes, Sander N. & Chappin, Maryse M.H., 2017. "Seduced into collaboration: A resource-based choice experiment to explain make, buy or ally strategies of SMEs," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 284-297.
    10. Ochieng’, Brian J. & Hobbs, Jill E., 2016. "Incentives for cattle producers to adopt an E. Coli vaccine: An application of best–worst scaling," Food Policy, Elsevier, vol. 59(C), pages 78-87.
    11. Aurélie Bertrand & Christian Hafner, 2014. "On heterogeneous latent class models with applications to the analysis of rating scores," Computational Statistics, Springer, vol. 29(1), pages 307-330, February.
    12. Frasquet, Marta & Ieva, Marco & Ziliani, Cristina, 2021. "Online channel adoption in supermarket retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    13. Jiao, Xi & Pouliot, Mariève & Walelign, Solomon Zena, 2017. "Livelihood Strategies and Dynamics in Rural Cambodia," World Development, Elsevier, vol. 97(C), pages 266-278.
    14. Grn, Bettina & Leisch, Friedrich, 2009. "Dealing with label switching in mixture models under genuine multimodality," Journal of Multivariate Analysis, Elsevier, vol. 100(5), pages 851-861, May.
    15. van Rijnsoever, Frank J. & Castaldi, Carolina & Dijst, Martin J., 2012. "In what sequence are information sources consulted by involved consumers? The case of automobile pre-purchase search," Journal of Retailing and Consumer Services, Elsevier, vol. 19(3), pages 343-352.
    16. van Wieringen, Wessel N., 2005. "On identifiability of certain latent class models," Statistics & Probability Letters, Elsevier, vol. 75(3), pages 211-218, December.
    17. Saeideh Khosroshahi & Lin Crase & Bethany Cooper & Michael Burton, 2021. "Matching customers’ preferences for tariff reform with managers’ appetite for change: The case of volumetric‐only tariffs in Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(2), pages 449-471, April.
    18. Tueanrat, Yanika & Papagiannidis, Savvas & Alamanos, Eleftherios, 2021. "A conceptual framework of the antecedents of customer journey satisfaction in omnichannel retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    19. Seuk Yen Phoong & Shi Ling Khek & Seuk Wai Phoong, 2022. "The Bibliometric Analysis on Finite Mixture Model," SAGE Open, , vol. 12(2), pages 21582440221, May.
    20. Baffour Bernard & Brown James J. & Smith Peter W.F., 2021. "Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses," Journal of Official Statistics, Sciendo, vol. 37(3), pages 673-697, September.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0071940. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.