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March 21, 2023
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December 31, 2022
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Estadística
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Resumen

Uno de los mayores avances en la investigación con métodos mixtos ha sido la conceptualización de uno o más tipos de análisis asociados con una tradición (por ejemplo, el análisis cualitativo) que se utilizan para analizar datos asociados con una tradición diferente (por ejemplo, datos cuantitativos), lo que Onwuegbuzie y Combs (2010) denominaron análisis mixtos cruzados o, más sencillamente, análisis cruzados. Una característica distintiva de los análisis cruzados es la noción de cuantificación, que, en su forma más simple, implica la conversión de datos cualitativos en formas numéricas que puedan analizarse estadísticamente. La cuantificación se ha centrado en enfoques descriptivos, como el recuento de temas emergentes. Lamentablemente, apenas existen orientaciones sobre la cuantificación inferencial, que se refiere a la cuantificación de datos cualitativos con fines de predicción o estimación. Aunque ha aparecido literatura reciente sobre unos pocos enfoques de cuantificación basados en la inferencia (es decir, análisis de regresión lineal múltiple, modelización de ecuaciones estructurales, modelización lineal jerárquica), todavía quedan algunos análisis de modelos lineales generales para los que los investigadores de métodos mixtos, en la búsqueda de la realización de análisis cruzados, pueden beneficiarse de las directrices. Uno de estos análisis es el análisis de correlación canónica. Su importancia radica en el hecho de que el análisis de datos cualitativos suele arrojar múltiples patrones de significado (ej., códigos, temas), que luego pueden correlacionarse con otras variables disponibles (ej., variables demográficas, variables de personalidad, variables afectivas) mediante el uso del análisis de correlación canónica. Por lo tanto, el propósito de este artículo es (a) describir el análisis de correlación canónica e (b) ilustrar cómo los análisis de correlación canónica pueden servir como cuantificación basada en la inferencia utilizando un ejemplo heurístico.

Palabras clave

temas emergentes investigación con métodos mixtos cuantificación basada en la descripción cuantificación basada en la exploración cuantificación basada en la inferencia cuantificación basada en la medición análisis de correlación canónica enfoque de integración 1 1 = 1 integración(es) completa(s)

Detalles del artículo

Cómo citar
Onwuegbuzie, A. J. (2022). Hacia la plena integración en la investigación con métodos mixtos: El papel del análisis de correlación canónica en la integración de datos cuantitativos y cualitativos. PUBLICACIONES, 52(2), 11–34. https://doi.org/10.30827/publicaciones.v52i2.27664
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Referencias

  1. Anderson, E. (1996). Introduction to the 1996 edition of The Philadelphia Negro. In W. E. B. DuBois, The Philadelphia Negro (pp. ix-xxxv). University of Pennsylvania Press.
  2. Anderson, M. T., Ingram, J. M., Buford, B. J., Rosli, R., Bledsoe, M. L., & Onwuegbuzie, A. J. (2012). Doctoral students’ perceptions of characteristics of effective college teachers: A mixed analysis. International Journal of Doctoral Studies, 7, 279-309. http://ijds.org/Volume7/IJDSv7p279-309Anderson0360.pdf
  3. Benge, C. L., Onwuegbuzie, A. J., Mallette, M. H., & Burgess, M. L. (2010). Doctoral students’ perceptions of barriers to reading empirical literature: A mixed analysis. International Journal of Doctoral Studies, 5, 55-77. https://doi.org/10.28945/1331
  4. Burgess, M. L., Benge, C. L., Onwuegbuzie, A. J., & Mallette, M. H. (2012). Doctoral students’ reasons for reading empirical research articles: A mixed analysis. Journal of Effective Teaching, 12(3), 5-33. http://www.uncw.edu/cte/et/articles/Vol12_3/Onwuegbuzie.pdf
  5. Cliff, N., & Krus, D. J. (1976). Interpretation of canonical analyses: Rotated vs. unrotated solutions. Psychometrica, 41, 35-42. https://doi.org/10.1007/BF02291696
  6. Collins, K. M. T., Onwuegbuzie, A. J., & Jiao, Q. G. (2007). A mixed methods investigation of mixed methods sampling designs in social and health science research. Journal of Mixed Methods Research, 1, 267-294. https://doi.org/10.1177/1558689807299526
  7. Daley, C. E., & Onwuegbuzie, A. J. (2004). Attributions toward violence of male juvenile delinquents: A concurrent mixed methods analysis. Journal of Social Psychology, 144, 549-570. https://doi.org/10.3200/SOCP.144.6.549-570
  8. Darlington, R. B., Weinberg, S. L., & Walberg, H. J. (1973). Canonical variate analysis
  9. and related techniques. Review of Educational Research, 42, 131-143. https://doi.org/10.3102/00346543043004433
  10. DuBois, W. E. B (1899). The Philadelphia Negro: A social study. University of Pennsylvania Press.
  11. Fetters M. D., & Freshwater, D. (2015). The 1 + 1 = 3 integration challenge. Journal of Mixed Methods Research, 9, 115-117. https://doi.org/10.1177/1558689815581222
  12. Fisher, R. A. (1922). On the interpretation of χ2 from contingency tables, and the calculation of P. Journal of the Royal Statistical Society, 85(1), 87-94. https://doi.org/10.2307/2340521. JSTOR 2340521
  13. Fisher, R. A. (1954). Statistical methods for research workers. Oliver and Boyd.
  14. Glaser, B. G. (1965). The constant comparative method of qualitative analysis. Social Problems, 12, 436-445. https://doi.org/10.1525/sp.1965.12.4.03a00070
  15. Henson, R. K. (2000). Demystifying parametric analyses: Illustrating canonical correlation as the multivariate general linear model. Multiple Linear Regression Viewpoints, 26, 11-19.
  16. Hesse-Biber, S. N. (2010). Mixed methods research: Merging theory and practice. Guilford Press.
  17. Hitchcock, J. H., & Onwuegbuzie, A. J. (2022). The Routledge handbook for advancing integration in mixed methods research: An introduction. In J. H. Hitchcock & A. J. Onwuegbuzie (Eds.), Routledge handbook for advancing integration in mixed methods research (pp. 3-27). Routledge.
  18. Johnson, R. B., & Gray, R. (2010). A history of philosophical and theoretical issues for mixed methods research. In A. Tashakkori & C. Teddlie (Eds.), Sage handbook of mixed methods in social and behavioral research (2nd ed., pp. 69-94). Sage.
  19. Knapp, T. R. (1978). Canonical correlation analysis: A general parametric significance
  20. testing system. Psychological Bulletin, 85, 410-416.
  21. https://doi.org/10.1037/0033-2909.85.2.410
  22. Leech, N. L., & Onwuegbuzie, A. J. (2008). Qualitative data analysis: A compendium of techniques and a framework for selection for school psychology research and beyond. School Psychology Quarterly, 23, 587-604. https://doi.org/10.1037/1045-3830.23.4.587
  23. Leech, N. L., & Onwuegbuzie, A. J. (in press). Teaching meta-themes: A mixed methods approach. In Wutich, A., Bernard, R., & Ruth, A. (Eds.), Handbook for teaching qualitative and mixed methods: A step-by-step guide. Routledge.
  24. LePlay, F. (1855). Les ouvriers européens [European workers]. Alfred Mame.
  25. Mason, J. (2006). Mixing methods in a qualitatively driven way. Qualitative Research, 6(1), 9-25. https://doi.org/10.1177/146879410605-8866
  26. Maxwell, J. (2016). Expanding the history and range of mixed methods research. Journal of Mixed Methods Research, 10(1), 12-27. https://doi.org/10.1177/1558689815571132
  27. McClure, D. R., Ojo, E. O., Schaefer, M B., Bell, D., Abrams, S. S., & Onwuegbuzie, A. J. (2021). Online learning challenges experienced by university students in the New York City area during the COVID-19 pandemic: A mixed methods study. International Journal of Multiple Research Approaches, 13(2), 150-167. https://doi.org/10.29034/ijmra.v13n2editorial4
  28. Miles, M., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Sage.
  29. Natesan, P., Onwuegbuzie, A. J., Hitchcock, J., & Newman, I. (2019). Fully Integrated Bayesian thinking: A mixed methods approach to the 1 + 1 = 1 formula. AERA Division D Newsletter, 10-12. http://www.aera.net/Portals/38/docs/DivD/DNews_current/DivDNewsletter_Spring19.pdf
  30. Newman, I., Onwuegbuzie, A. J., & Hitchcock, J. H. (2015). Using the general linear model to facilitate the full integration of qualitative and quantitative analysis: The potential to improve prediction and theory building and testing. General Linear Model Journal, 41(1), 12-28. http://www.glmj.org/archives/articles/Newman_v41n1.pdf
  31. Onwuegbuzie, A. J. (2012). Introduction: Putting the mixed back into quantitative and qualitative research in educational research and beyond: Moving towards the radical middle. International Journal of Multiple Research Approaches, 6(3), 192-219. https://doi.org/10.5172/mra.2012.6.3.192
  32. Onwuegbuzie, A. J. (2017, March). Mixed methods is dead! Long live mixed methods! Invited keynote address presented at the Mixed Methods International Research Association Caribbean Conference at Montego Bay, Jamaica.
  33. Onwuegbuzie, A, J. (2021). Beyond identifying emergent themes in mixed methods research studies: The role of economic indices: The Thematic Herfindahl-Hirschman Index and the Thematic Concentration Ratio. International Journal of Multiple Research Approaches, 13(2), 137-149. https://doi.org/10.29034/ijmra.v13n2editorial3
  34. Onwuegbuzie, A. J. (2022, October 13). Mixed methods research—where do we go from here?: The role of meta-methods research in the fourth and fifth industrial revolutions. An invited public lecture presented on behalf of the Mixed Methods International Research Association-Caribbean Chapter (MMIRA-CC) to honour the memory and work of the late Dr. Vimala Judy Kamalodeen.
  35. Onwuegbuzie, A. J. (in press). On quantitizing revisited. International Journal of Multiple Research Approaches.
  36. Onwuegbuzie, A. J., Abrams, S. S., & Forzani, E. (in press). The many SIDES of critical dialectical pluralism: A meta-philosophy—comprising a research philosophy, educational philosophy, and life philosophy—for addressing social justice, inclusion, diversity, and equity, and social responsibility. International Journal of Multiple Research Approaches.
  37. Onwuegbuzie, A. J., & Combs, J. P. (2010). Emergent data analysis techniques in mixed
  38. methods research: A synthesis. In A. Tashakkori & C. Teddlie (Eds.),
  39. Sage handbook of mixed methods in social and behavioral research (2nd ed., pp. 397-
  40. . Sage.
  41. Onwuegbuzie, A. J., & Daniel, L. G. (2003, February 12). Typology of analytical and interpretational errors in quantitative and qualitative educational research. Current Issues in Education [On-line], 6(2). https://cie.asu.edu/ojs/index.php/cieatasu/article/view/1609/651
  42. Onwuegbuzie, A. J., Forzani, E., & Abrams, J. (2022). History of quantitative, qualitative, mixed methods research, and educational assessment: A review. Unpublished manuscript, University of Cambridge, Cambridge, England.
  43. Onwuegbuzie, A. J., & Frels, R. K. (2013). Introduction: Towards a new research philosophy for addressing social justice issues: Critical dialectical pluralism 1.0. International Journal of Multiple Research Approaches, 7, 9-26. https://doi.org/10.5172/mra.2013.7.1.9
  44. Onwuegbuzie, A. J., Gerber, H. R., & Abrams, S. S. (2017). Mixed methods research. The International Encyclopedia of Communication Research Methods, 1-33. https://doi.org/10.1002/9781118901731.iecrm0156
  45. Onwuegbuzie, A. J., & Hitchcock, J. H. (2019). Toward a fully integrated approach to mixed methods research via the 1 + 1 = 1 integration approach: Mixed Research 2.0. International Journal of Multiple Research Approaches, 11(1), 7-28. https://doi.org/10.29034/ijmra.v11n1editorial1
  46. Onwuegbuzie, A. J., & Johnson, R. B. (2021a). Mapping the emerging landscape of mixed analysis. In A. J. Onwuegbuzie & R. B. Johnson (Eds.), The Routledge reviewer’s guide to mixed methods analysis (pp. 1-22). Routledge.
  47. Onwuegbuzie, A. J., & Johnson, R. B. (2021b). The Routledge reviewer’s guide to mixed methods analysis. Routledge.
  48. Onwuegbuzie, A. J., & Leech, N. L. (2019). On qualitizing. International Journal of Multiple Research Approaches, 11, 98-131. https://doi.org/10.29034/ijmra.v11n2editorial2
  49. Onwuegbuzie, A. J., & Leech, N. L. (2021). Qualitizing data. In A. J. Onwuegbuzie & R. B. Johnson (Eds.), The Routledge reviewer’s guide to mixed analysis (pp. 239-258). Routledge.
  50. Onwuegbuzie, A. J., Mallette, M. H., & Mallette, K. M. (2023). A 41-year history of mixed methods research in education: A mixed methods bibliometric study of published works from 1980 to 2021. Journal of Mixed Method Studies, 5.
  51. Onwuegbuzie, A. J., & Ojo, E. O. (2021). University students’ experiences of learning in an online environment in COVID-19 pandemic: A meta-methods research study of perceptions and attitudes of South African students. Journal of Pedagogical Research, 5(4), 1-18. https://doi.org/10.33902/JPR.C
  52. Onwuegbuzie, A. J., Ojo, E. O., Burger, A., Crowley, T., Adams, S. P., & Bergsteedt, B. T. (2020). Challenges experienced by students at Stellenbosch University that hinder their ability successfully to learn online during the COVID-19 era: A demographic and spatial analysis. International Journal of Multiple Research Approaches, 12(3), 240-281. https://doi.org/10.29034/ijmra.v12n3editorial2
  53. Onwuegbuzie, A. J., & Teddlie, C. (2003). A framework for analyzing data in mixed methods research. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 351-383). Sage.
  54. Onwuegbuzie, A. J., Witcher, A. E., Collins, K. M. T., Filer, J. D., Wiedmaier, C. D., & Moore, C. W. (2007). Students’ perceptions of characteristics of effective college teachers: A validity study of a teaching evaluation form using a mixed methods analysis. American Educational Research Journal, 44, 113-160. https://doi.org/10.3102/0002831206298169
  55. Parkhurst, P. E., Lovell, K. L., Sprafka, S. A., & Hodgins, M. (1972). Evaluation of videodisc modules: A mixed methods approach. (ERIC Document Reproduction Service No. ED348014)
  56. Roberts, J. K., & Henson, R. K. (2002). Correction for bias in estimating effect sizes.
  57. Educational and Psychological Measurement, 62, 241-253.
  58. https://doi.org/10.1177/0013164402062002003
  59. Sandelowski, M., Voils, C. I., & Knafl, G. (2009). On quantitizing. Journal of Mixed Methods Research, 3, 208-222. https://doi.org/10.1177/1558689809334210
  60. Tashakkori, A., & Teddlie, C. (1998). Mixed methodology: Combining qualitative and quantitative approaches. Applied Social Research Methods Series (Vol. 46). Sage.
  61. Teddlie, C., & Johnson, R. B. (2009). Methodological thought since the 20th century. In C.
  62. Teddlie & A. Tashakkori, Foundations of mixed methods research: Integrating quantitative and qualitative techniques in the social and behavioral sciences (pp. 62-82). Sage.
  63. Thompson, B. (1984). Canonical correlation analysis: Uses and interpretations. Sage.
  64. Thompson, B. (1991). Methods, plainly speaking: A primer on the logic and use of
  65. canonical correlation analysis. Measurement and Evaluation in Counseling and Development, 24, 80-93.
  66. Witcher, A. E., Jiao, Q. G., Onwuegbuzie, A. J., Collins, K. M. T., James, T. L., & Minor, L. C. (2008). Preservice teachers’ perceptions of characteristics of an effective teacher as a function of discipline orientation: A mixed methods investigation. The Teacher Educator, 43, 279-301. https://doi.org/10.1080/08878730802247852
  67. Witcher, A. E., Onwuegbuzie, A. J., & Minor, L. C. (2001). Characteristics of effective teachers: Perceptions of preservice teachers. Research in the Schools, 8(2), 45-57.
  68. Wutich, A., Beresford, M., SturtzSreetharan, C., Brewis, A., Trainer, S., & Hardin, J. (2021). Metatheme analysis: A qualitative method for cross-cultural research. International Journal of Qualitative Methods, 20, 1-11. https://doi.org/10.1177/1609406921101990.