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Bayesian Hierarchical Factor Analysis for Eficient Estimation Across Race/Ethnicity

  • Autores: Jiexiang Hu, Lauren Clark, Peng Shi, Vincent S. Staggs, Christine M. Daley, Byron J Gajewski
  • Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 44, Nº. 2, 2021, págs. 313-329
  • Idioma: inglés
  • DOI: 10.15446/rce.v44n2.87690
  • Títulos paralelos:
    • Estimación eficiente a través de raza y etnicidad usando análisis factorial jerárquico bayesiano
  • Enlaces
  • Resumen
    • español

      Resumen Las repuestas reportadas por el paciente están siendo fuertemente consideradas en la investigación de respuestas de salud centradas en el paciente y en estudios de calidad de vida comos indicadores importantes de respuestas clínicas, especialmente en pacientes con enfermedades crónicas. El análisis factorial es ideal para medir respuestas reportadas por el paciente. Cuando hay heterogeneidad en la población de pacientes y el tamaño muestral es pequeño, diferencias en el funcionamiento de los ítems y problemas de convergencia plantean dificultades para aplicar modelos factoriales. El análisis factorial jerárquico Bayesiano puede evaluar disparidades de salud evaluando el funcionamiento diferencial de los ítems, mientras que evita problemas de convergencia. Hemos realizado un estudio de simulación y empleado un ejemplo empírico con minorías indígenas Americanas para mostrar que el ajuste de un modelo factorial jerárquico Bayesiano es una solución óptima sin importar la heterogeneidad de la población o el tamaño muestral.

    • English

      Abstract Patient reported outcomes are gaining more attention in patient-centered health outcomes research and quality of life studies as important indicators of clinical outcomes, especially for patients with chronic diseases. Factor analysis is ideal for measuring patient reported outcomes. If there is heterogeneity in the patient population and when sample size is small, differential item functioning and convergence issues are challenges for applying factor models. Bayesian hierarchical factor analysis can assess health disparity by assessing for differential item functioning, while avoiding convergence problems. We conducted a simulation study and used an empirical example with American Indian minorities to show that fitting a Bayesian hierarchical factor model is an optimal solution regardless of heterogeneity of population and sample size.

  • Referencias bibliográficas
    • Asparouhov, T.,Muthén, B. (2010). 'Bayesian analysis of latent variable models using mplus'.
    • Basch, E.,Bennett, A.,Pietanza, M. C. (2011). 'Use of patient-reported outcomes to improve the predictive accuracy of clinician-reported...
    • Bell, S. A.,Smith, C. T. (2014). 'A comparison of interventional clinical trials in rare versus non-rare diseases: an analysis of clinicaltrials....
    • Calvert, M.,Kyte, D.,Mercieca-Bebber, R.,Slade, A.,Chan, A.-W.,King, M. T.,Hunn, A.,Bottomley, A.,Regnault, A.,Ells, C.. (2018). 'Guidelines...
    • Cella, D.,Riley, W.,Stone, A.,Rothrock, N.,Reeve, B.,Yount, S.,Amtmann, D.,Bode, R.,Buysse, D.,Choi, S.. (2010). 'The patient-reported...
    • (2021). Centers for Disease Control and Prevention. 'About chronic diseases'..
    • Chaloner, K. (1987). 'A bayesian approach to the estimation of variance components for the unbalanced one-way random model'. Technometrics....
    • Cuijpers, P.,Li, J.,Hofmann, S. G.,Andersson, G. (2010). 'Self-reported versus clinician-rated symptoms of depression as outcome measures...
    • Dawson, J.,Doll, H.,Fitzpatrick, R.,Jenkinson, C.,Carr, A. J. (2010). 'The routine use of patient reported outcome measures in healthcare...
    • Deshpande, P. R.,Rajan, S.,Sudeepthi, B. L.,Nazir, C. A. (2011). 'Patientreported outcomes: a new era in clinical research'. Perspectives...
    • Doward, L. C.,Gnanasakthy, A.,Baker, M. G. (2010). 'Patient reported outcomes: looking beyond the label claim'. Health and quality...
    • Drasgow, F. (1987). 'Study of the measurement bias of two standardized psychological tests.'. Journal of Applied psychology. 72. 19
    • Engelman, K. K.,Daley, C. M.,Gajewski, B. J.,Ndikum-Mo-or, F.,Faseru, B.,Braiuca, S.,Joseph, S.,Ellerbeck, E. F.,Greiner, K. A. (2010). 'An...
    • (2016). European Medicines Agency. 'Guideline on the evaluation of anticancer medicinal products in man: The use of patient-reported outcome...
    • (2016). FDA-NIH Biomarker Working Group. 'Best (biomarkers, endpoints, and other tools) resource.
    • Frost, M. H.,Reeve, B. B.,Liepa, A. M.,Stau_er, J. W.,Hays, R. D.,Group, M. P.-R. O. C. M. (2007). 'What is suficient evidence for the...
    • Gajewski, B. J.,Meinzer, C.,Berry, S. M.,Rockswold, G. L.,Barsan, W. G.,Korley, F. K.,Martin, R. (2019). 'Bayesian hierarchical emax model...
    • Gamerman, D.,Lopes, H. F. (2006). Markov chain Monte Carlo: stochastic simulation for Bayesian inference. CRC Press.
    • Garrard, L.,Price, L. R.,Bott, M. J.,Gajewski, B. J. (2015). 'A novel method for expediting the development of patient-reported outcome...
    • Gelman, A.,Carlin, J. B.,Stern, H. S.,Dunson, D. B.,Vehtari, A.,Rubin, D. B. (2013). Bayesian data analysis. CRC press.
    • Gelman, A.,Hill, J.,Yajima, M. (2012). 'Why we (usually) don't have to worry about multiple comparisons'. Journal of Research...
    • Gelman, A.. (2006). 'Prior distributions for variance parameters in hierarchical models (comment on article by browne and draper)'....
    • Ghosh, J.,Dunson, D. B. (2008). Bayesian model selection in factor analytic models, in 'Random effect and latent variable model selection'....
    • Gilks, W.,Richardson, S.,Spiegelhalter, D. (1996). 'Markov chain monte carlo in practice chapman and hallcrc'.
    • Hoofs, H.,van de Schoot, R.,Jansen, N. W.,Kant, I. (2018). 'Evaluating model fit in bayesian confirmatory factor analysis with large samples:...
    • Jiang, Y.,Boyle, D. K.,Bott, M. J.,Wick, J. A.,Yu, Q.,Gajewski, B. J. (2014). 'Expediting clinical and translational research via bayesian...
    • Joreskog, K. G.,Dag, S.,Magidson, J. (1979). Advances in factor analysis and structural equation models, Abt books.
    • Jöreskog, K. G.,Goldberger, A. S. (1975). 'Estimation of a model with multiple indicators and multiple causes of a single latent variable'....
    • Kemp, C.,Perfors, A.,Tenenbaum, J. B. (2007). 'Learning overhypotheses with hierarchical bayesian models'. Developmental science....
    • Kruschke, J. (2011). Tutorial: Doing bayesian data analysis with r and bugs. 33. 'Proceedings of the Annual Meeting of the Cognitive...
    • Kwok, H.,Lewis, R. J. (2011). 'Bayesian hierarchical modeling and the integration of heterogeneous information on the effectiveness of...
    • Lee, S.-Y. (2007). Structural equation modeling: A Bayesian approach. John Wiley & Sons.
    • Lunn, D. J.,Thomas, A.,Best, N.,Spiegelhalter, D. (2000). 'Winbugs-a bayesian modelling framework: concepts, structure, and extensibility'....
    • Lynch, S. M. (2007). Introduction to applied Bayesian statistics and estimation for social scientists. Springer Science & Business Media....
    • MacCallum, R. C.,Austin, J. T. (2000). 'Applications of structural equation modeling in psychological research'. Annual review of...
    • MacCallum, R. C.,Roznowski, M.,Necowitz, L. B. (1992). 'Model modifications in covariance structure analysis: the problem of capitalization...
    • Marsh, H. W.,Muthén, B.,Asparouhov, T.,Lüdtke, O.,Robitzsch, A.,Morin, A. J.,Trautwein, U. (2009). 'Exploratory structural equation modeling,...
    • McNeish, D. (2016). 'On using bayesian methods to address small simple problems'. Structural Equation Modeling: A Multidisciplinary...
    • Muthén, B. (2010). 'Bayesian analysis in mplus: A brief introduction'.
    • Muthén, B.,Asparouhov, T. (2012). 'Bayesian structural equation modeling: a more flexible representation of substantive theory.'....
    • Muthén, B. O. (2002). 'Beyond sem: General latent variable modeling'. Behaviormetrika. 29. 81-117
    • (2019). National Institutes of Health. 'Patient-reported outcomes measurement information system (promis)'.
    • Ndikum-Moffor, F. M.,Braiuca, S.,Daley, C. M.,Gajewski, B. J.,Engelman, K. K. (2013). 'Assessment of mammography experiences and satisfaction...
    • Press, S. J. (2009). Subjective and objective Bayesian statistics: Principles, models, and applications. John Wiley & Sons.
    • Samaniego, F. J.,Reneau, D. M. (1994). 'Toward a reconciliation of the bayesian and frequentist approaches to point estimation'. Journal...
    • Sanderson, T.,Kirwan, J. (2009). 'Patient-reported outcomes for arthritis: Time to focus on personal life impact measures?'.
    • Scheines, R.,Hoijtink, H.,Boomsma, A. (1999). 'Bayesian estimation and testing of structural equation models'. Psychometrika. 64....
    • Sturtz, S.,Ligges, U.,Gelman, A. E. (2005). 'R2winbugs: a package for running winbugs from r'.
    • Swaminathan, H.,Rogers, H. J. (1990). 'Detecting differential item functioning using logistic regression procedures'. Journal of Educational...
    • Thissen, D. (1988). 'Use of item response theory in the study of group differences in trace lines'. Test validity.
    • Tunis, S. R.,Stryer, D. B.,Clancy, C. M. (2003). 'Practical clinical trials: increasing the value of clinical research for decision making...
    • (2020). US Food & Drug Administration. 'Fda patient-focused drug development guidance series for enhancing the incorporation of the...
    • (2009). US Food and Drug Administration. 'Guidance for industry: Patientreported outcome measures: Use in medical product development...
    • Wainer, H.,Braun, H. (1988). 'Differential item performance and the mantelhaenszel procedure'. Test Validity. 129
    • Ware Jr, J.,Kosinski, M.,Bjorner, J. (2004). 'Item banking and the improvement of health status measures'. Quality of Life. 2-5
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