Skip to main content
Erschienen in: Quality of Life Research 9/2013

01.11.2013 | Commentary

Pitfalls in subgroup analysis based on growth mixture models: a commentary on van Leeuwen et al. (2012)

verfasst von: Cameron N. McIntosh

Erschienen in: Quality of Life Research | Ausgabe 9/2013

Einloggen, um Zugang zu erhalten

Abstract

Objectives

This article is a brief commentary in response to “van Leeuwen et al. (Qual Life Res 21:1499–1508, 2012)”

Methods and results

The commentary argues that in the context of mixture modeling, assigning individuals to specific subgroups for conducting a secondary set of analyses ignores the original uncertainty in group membership, thereby biasing any subsequent results and inference.

Conclusions

Alternative approaches to subgroup analysis that attempt to preserve uncertainty in group membership are discussed and illustrated.
Anhänge
Nur mit Berechtigung zugänglich
Literatur
1.
Zurück zum Zitat Sprangers, M. A., & Schwartz, C. E. (1999). Integrating response shift into health-related quality of life research: A theoretical model. Social Science and Medicine, 48, 1507–1515.PubMedCrossRef Sprangers, M. A., & Schwartz, C. E. (1999). Integrating response shift into health-related quality of life research: A theoretical model. Social Science and Medicine, 48, 1507–1515.PubMedCrossRef
2.
Zurück zum Zitat Schwartz, C. E., & Sprangers, M. A. G. (Eds.). (2000). Adaptation to changing health: Response shift in quality-of-life research. Washington, D.C: American Psychological Association. Schwartz, C. E., & Sprangers, M. A. G. (Eds.). (2000). Adaptation to changing health: Response shift in quality-of-life research. Washington, D.C: American Psychological Association.
3.
Zurück zum Zitat Schwartz, C. E., Bode, R., Repucci, N., Becker, J., Sprangers, M. A., & Fayers, P. M. (2006). The clinical significance of adaptation to changing health: A meta-analysis of response shift. Quality Life Research, 15(9), 1533–1550.CrossRef Schwartz, C. E., Bode, R., Repucci, N., Becker, J., Sprangers, M. A., & Fayers, P. M. (2006). The clinical significance of adaptation to changing health: A meta-analysis of response shift. Quality Life Research, 15(9), 1533–1550.CrossRef
4.
Zurück zum Zitat Rapkin, B. D., & Schwartz, C. E. (2004). Toward a theoretical model of quality-of-life appraisal: Implications of findings from studies of response shift. Health and Quality of Life Outcomes, 2, 14.PubMedCrossRef Rapkin, B. D., & Schwartz, C. E. (2004). Toward a theoretical model of quality-of-life appraisal: Implications of findings from studies of response shift. Health and Quality of Life Outcomes, 2, 14.PubMedCrossRef
5.
Zurück zum Zitat Howard, J. S., Mattacola, C. G., Howell, D. M., & Lattermann, C. (2011). Response shift theory: An application for health-related quality of life in rehabilitation research and practice. Journal of Allied Health, 40(1), 31–38.PubMed Howard, J. S., Mattacola, C. G., Howell, D. M., & Lattermann, C. (2011). Response shift theory: An application for health-related quality of life in rehabilitation research and practice. Journal of Allied Health, 40(1), 31–38.PubMed
6.
Zurück zum Zitat Oort, F., Visser, M., & Sprangers, M. (2009). Formal definitions of measurement bias and explanation bias clarify measurement and conceptual perspectives on response shift. Journal of Clinical Epidemiology, 62(11), 1126–1137.PubMedCrossRef Oort, F., Visser, M., & Sprangers, M. (2009). Formal definitions of measurement bias and explanation bias clarify measurement and conceptual perspectives on response shift. Journal of Clinical Epidemiology, 62(11), 1126–1137.PubMedCrossRef
7.
Zurück zum Zitat Nieuwkerk, P. T., Tollenaar, M. S., Oort, F. J., & Sprangers, M. A. (2007). Are retrospective measures of change in quality of life more valid than prospective measures? Medical Care, 45(3), 199–205.PubMedCrossRef Nieuwkerk, P. T., Tollenaar, M. S., Oort, F. J., & Sprangers, M. A. (2007). Are retrospective measures of change in quality of life more valid than prospective measures? Medical Care, 45(3), 199–205.PubMedCrossRef
8.
Zurück zum Zitat Lau, D., Agborsangaya, C., Sayah, F. A., Wu, X., Ohinmaa, A., & Johnson, J. A. (2012). Population-level response shift: Novel implications for research. Quality of Life Research, 21(9), 1495–1498 Lau, D., Agborsangaya, C., Sayah, F. A., Wu, X., Ohinmaa, A., & Johnson, J. A. (2012). Population-level response shift: Novel implications for research. Quality of Life Research, 21(9), 1495–1498
9.
Zurück zum Zitat Schwartz, C. E., Andresen, E. M., Nosek, M. A., Krahn, G. L., & the RRTC Expert Panel on Health Status Management. (2007). Response shift theory: Important implications for measuring quality of life in people with disability. Archives of Physical Medicine and Rehabilitation, 88(4), 529–536 Schwartz, C. E., Andresen, E. M., Nosek, M. A., Krahn, G. L., & the RRTC Expert Panel on Health Status Management. (2007). Response shift theory: Important implications for measuring quality of life in people with disability. Archives of Physical Medicine and Rehabilitation, 88(4), 529–536
10.
Zurück zum Zitat Kievit, W., Hendrikx, J., Stalmeier, P. F., van de Laar, M. A., Van Riel, P. L., & Adang, E. M. (2010). The relationship between change in subjective outcome and change in disease: A potential paradox. Quality of Life Research, 19(7), 985–994.PubMedCrossRef Kievit, W., Hendrikx, J., Stalmeier, P. F., van de Laar, M. A., Van Riel, P. L., & Adang, E. M. (2010). The relationship between change in subjective outcome and change in disease: A potential paradox. Quality of Life Research, 19(7), 985–994.PubMedCrossRef
11.
Zurück zum Zitat Ubel, P. A., Peeters, Y., & Smith, D. (2010). Abandoning the language of ‘‘response shift’’: A plea for conceptual clarity in distinguishing scale recalibration from true changes in quality of life. Quality of Life Research, 19, 465–471.PubMedCrossRef Ubel, P. A., Peeters, Y., & Smith, D. (2010). Abandoning the language of ‘‘response shift’’: A plea for conceptual clarity in distinguishing scale recalibration from true changes in quality of life. Quality of Life Research, 19, 465–471.PubMedCrossRef
12.
Zurück zum Zitat Nolte, S., Elsworth, G. R., Sinclair, A. J., & Osborne, R. H. (2012). The inclusion of ‘then-test’ questions in post-test questionnaires alters post-test responses: A randomized study of bias in health program evaluation. Quality of Life Research, 21(3), 487–494.PubMedCrossRef Nolte, S., Elsworth, G. R., Sinclair, A. J., & Osborne, R. H. (2012). The inclusion of ‘then-test’ questions in post-test questionnaires alters post-test responses: A randomized study of bias in health program evaluation. Quality of Life Research, 21(3), 487–494.PubMedCrossRef
13.
Zurück zum Zitat van Leeuwen, C. M. C., Post, M. W. M., van der Woude, L. H. V., de Groot, S., Smit, C., van Kuppevelt, D., et al. (2012). Changes in life satisfaction in persons with spinal cord injury during and after inpatient rehabilitation: adaptation or measurement bias? Quality of Life Research, 21, 1499–1508.PubMedCrossRef van Leeuwen, C. M. C., Post, M. W. M., van der Woude, L. H. V., de Groot, S., Smit, C., van Kuppevelt, D., et al. (2012). Changes in life satisfaction in persons with spinal cord injury during and after inpatient rehabilitation: adaptation or measurement bias? Quality of Life Research, 21, 1499–1508.PubMedCrossRef
14.
Zurück zum Zitat van Leeuwen, C. M., Post, M. W., Hoekstra, T., van der Woude, L. H., de Groot, S., Snoek, G. J., et al. (2011). Trajectories in the course of life satisfaction after spinal cord injury: Identification and predictors. Archives of Physical Medicine and Rehabilitation, 92(2), 207–213.PubMedCrossRef van Leeuwen, C. M., Post, M. W., Hoekstra, T., van der Woude, L. H., de Groot, S., Snoek, G. J., et al. (2011). Trajectories in the course of life satisfaction after spinal cord injury: Identification and predictors. Archives of Physical Medicine and Rehabilitation, 92(2), 207–213.PubMedCrossRef
15.
Zurück zum Zitat Muthén, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Newbury Park, CA: Sage. Muthén, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Newbury Park, CA: Sage.
16.
Zurück zum Zitat Muthen, B. O., & Asparouhov, T. (2008). Growth mixture modeling: Analysis with non-Gaussian random effects. In G. Fitzmaurice, M. Davidian, G. Verbeke, & G. Molenberghs (eds.), Longitudinal data analysis (pp. 143–165). Boca Raton: Chapman & Hall/CRC Press. Muthen, B. O., & Asparouhov, T. (2008). Growth mixture modeling: Analysis with non-Gaussian random effects. In G. Fitzmaurice, M. Davidian, G. Verbeke, & G. Molenberghs (eds.), Longitudinal data analysis (pp. 143–165). Boca Raton: Chapman & Hall/CRC Press.
17.
Zurück zum Zitat Peugh, J., & Fan, X. (2012). How well does growth mixture modeling identify heterogeneous growth trajectories? A simulation study examining GMM’s performance characteristics. Structural Equation Modeling, 19(2), 204–226.CrossRef Peugh, J., & Fan, X. (2012). How well does growth mixture modeling identify heterogeneous growth trajectories? A simulation study examining GMM’s performance characteristics. Structural Equation Modeling, 19(2), 204–226.CrossRef
18.
Zurück zum Zitat Clogg, C. C. (1995). Latent class models: Recent developments and prospects for the future. In G. Arminger, C. C. Clogg, & M. E. Sobel (Eds.), Handbook of statistical modeling for the social and behavioral sciences (pp. 311–352). New York: Plenum.CrossRef Clogg, C. C. (1995). Latent class models: Recent developments and prospects for the future. In G. Arminger, C. C. Clogg, & M. E. Sobel (Eds.), Handbook of statistical modeling for the social and behavioral sciences (pp. 311–352). New York: Plenum.CrossRef
21.
Zurück zum Zitat Bolck, A., Croon, M. A., & Hagenaars, J. A. (2004). Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political Analysis, 12(1), 3–27.CrossRef Bolck, A., Croon, M. A., & Hagenaars, J. A. (2004). Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political Analysis, 12(1), 3–27.CrossRef
22.
Zurück zum Zitat Lanza, S. T., Tan, X., & Bray, B. C. (2013). Latent class analysis with distal outcomes: A flexible model-based approach. Structural Equation Modeling, 20(1), 1–26. Lanza, S. T., Tan, X., & Bray, B. C. (2013). Latent class analysis with distal outcomes: A flexible model-based approach. Structural Equation Modeling, 20(1), 1–26.
23.
Zurück zum Zitat Li, L., & Hser, Y.-I. (2011). On inclusion of covariates for class enumeration of growth mixture models. Multivariate Behavioral Research, 46(2), 266–302.PubMedCrossRef Li, L., & Hser, Y.-I. (2011). On inclusion of covariates for class enumeration of growth mixture models. Multivariate Behavioral Research, 46(2), 266–302.PubMedCrossRef
24.
Zurück zum Zitat Petras, H., & Masyn, K. (2010). General growth mixture analysis with antecedents and consequences of change. In A. Piquero & D. Weisburd (Eds.), Handbook of quantitative criminology (pp. 69–100). New York: Springer.CrossRef Petras, H., & Masyn, K. (2010). General growth mixture analysis with antecedents and consequences of change. In A. Piquero & D. Weisburd (Eds.), Handbook of quantitative criminology (pp. 69–100). New York: Springer.CrossRef
25.
Zurück zum Zitat Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18(4), 450–469.CrossRef Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18(4), 450–469.CrossRef
26.
Zurück zum Zitat Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. New York, NY: Wiley. Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. New York, NY: Wiley.
27.
Zurück zum Zitat Chung, H., Lanza, S. T., & Loken, E. (2008). Latent transition analysis: Inference and estimation. Statistics in Medicine, 27, 1834–1854.PubMedCrossRef Chung, H., Lanza, S. T., & Loken, E. (2008). Latent transition analysis: Inference and estimation. Statistics in Medicine, 27, 1834–1854.PubMedCrossRef
28.
Zurück zum Zitat Bakk, Z., Tekle, F. B., & Vermunt, J. K. (2011). Estimating the association between latent class membership and external variables using bias adjusted three-step approaches. Technical Report. Tilburg, The Netherlands: Tilburg University. Accessed February 13, 2013 at http://members.home.nl/jeroenvermunt/bakk2011.pdf. Bakk, Z., Tekle, F. B., & Vermunt, J. K. (2011). Estimating the association between latent class membership and external variables using bias adjusted three-step approaches. Technical Report. Tilburg, The Netherlands: Tilburg University. Accessed February 13, 2013 at http://​members.​home.​nl/​jeroenvermunt/​bakk2011.​pdf.
Metadaten
Titel
Pitfalls in subgroup analysis based on growth mixture models: a commentary on van Leeuwen et al. (2012)
verfasst von
Cameron N. McIntosh
Publikationsdatum
01.11.2013
Verlag
Springer Netherlands
Erschienen in
Quality of Life Research / Ausgabe 9/2013
Print ISSN: 0962-9343
Elektronische ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-013-0385-x

Weitere Artikel der Ausgabe 9/2013

Quality of Life Research 9/2013 Zur Ausgabe