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

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  • 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
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    References listed on IDEAS

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    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.
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