Measurement Validity

This page focuses on validity and methods for measuring health and quality of life in diverse populations using patient-reported outcomes (PROs).

The resources address the following measurement validity questions:

What are the challenges and solutions when using PROs to evaluate change and compare different people?

  1.  Whiteboard Video (3-mins long)
  2. This 3-part whiteboard video provides a brief introduction to:

    • Part 1: Use of Patient-Reported Outcomes Measures in healthcare
    • Part 2: Response shift: How do we ensure valid assessments of change over time?
    • Part 3: Differential item functioning: How do we ensure valid comparisons of different people?

  3.  Webinar on Interpretation of PROs in clinical practice:
    Solutions for assessing change and diverse people
    | ISOQOL (June 16)

  1.  Independent Online Learning Module
  2. Learn about latent variable methods for examining measurement invariance when comparing patient-reported outcomes between groups and over time.

    This learning module introduces latent variable methods for examining measurement invariance between groups and over time, and the related concepts of differential item functioning and response shift. The learning module provides a basic introduction with expository analyses and syntax for implementing:

    • Differential item functioning methods to compare different people
    • Response shift methods to assess change over time

    The module is meant as an initial introduction for applied researchers and analysts to become familiar with statistical methods for testing psychometric validity of using PROs to compare different people and assessing change over time.

    Learing Module Start Screen

    Note: this is a preliminary version of the learning module that is in process of ongoing development, with plans for further refinement and new resources to be added. Please help us to evaluate and improve the resources by completing a short survey after reviewing the module: Measurement Invariance Methods for PROs Learning Module Feedback Survey

  3. Data, Syntax and Resources
  4. The learning module includes expository analyses with access to data file, annotated MPlus input and output files, software package information for SAS and R and resources.

Our Team (PDF - 1 pg, 107 KB)

Practical Implications

  •  Publication: Sawatzky, R., Kwon, J.-Y., Barclay, R., Chauhan, C., Frank, L., van den Hout, W. B., Nielsen, L. K., Nolte, S., Sprangers, M. A. G., & the Response Shift – in Sync Working, G. (2021, 2021/03/02). Implications of response shift for micro-, meso-, and macro-level healthcare decision-making using results of patient-reported outcome measures. Quality of Life Research.

Theoretical Foundations

  •  Presentation: Sawatzky, R. (2017, April 19). Relating modern perspectives of measurement validation to the justification of inferences based on PRO scores. National Cancer Institute Outcomes Research Branch (ORB) Virtual Speaker Series Webinar. Available from:

  •  Publication: Sawatzky, R., Chan, E. K. H., Zumbo, B. D., Ahmed, S., Bartlett, S. J., Bingham, C. O., 3rd, Gardner, W., Jutai, J., Kuspinar, A., Sajobi, T., & Lix, L. M. (2017, Sep). Montreal Accord on Patient-Reported Outcomes (PROs) use series-Paper 7: Modern perspectives of measurement validation emphasize justification of inferences based on patient reported outcome scores. J Clin Epidemiol, 89, 154-159.

  •  Publication: Kwon, J. Y., Thorne, S., & Sawatzky, R. (2019, Mar). Interpretation and use of patient-reported outcome measures through a philosophical lens. Qual Life Res, 28(3), 629-636.

Analytical Methods

  •  Sébille, V., Lix, L. M., Ayilara, O. F., Sajobi, T. T., Janssens, A. C. J. W., Sawatzky, R., Sprangers, M. A. G., & Verdam, M. G. E. (2021). Critical examination of current response shift methods and proposal for advancing new methods. Quality of Life Research.

  •  Sawatzky, R., Sajobi, T. T., Brahmbhatt, R., Chan, E. K. H., Lix, L. M. & Zumbo, B. D. (2017). Longitudinal change in response processes: A response shift perspective. In Zumbo, B. D., Hubley, A. M. Understanding and investigating response processes in validation research. (pp. 251-276). New York: Springer.

  •  Sajobi, T. T., Brahmbatt, R., Lix, L. M., Zumbo, B. D., & Sawatzky, R. (2017). Scoping review of response shift methods: Current reporting practices and recommendations. Quality of Life Research, 27(5), 1133-1146. doi: 10.1007/s11136-017-1751-x

  •  Sawatzky, R., Russell, L. B., Sajobi. T. T., Lix. L. M., Kopec, J. A., & Zumbo, B. D., (2017). The use of latent variable mixture models to identify invariant items in test construction. Quality of Life Research, 27(7), 1745-1755. doi: 10.1007/s11136-017-1680-8

  •  Wu, X., Sawatzky, R., Hopman, W., Mayo, N., Sajobi, T. T., Liu, J., Prior, J., Papaioannou, A., Josse, R. G., Towheed, T., Davison, K. S., & Lix, L. M. (2017). Latent variable mixture models to test for differential item functioning: A population-based analysis. Health and Quality of Life Outcomes, 15, 102. doi: 10.1186/s12955-017-0674-0

  •  Lix, L. M., Wu, X., Hopman, W., Mayo, N., Sajobi, T. T., Liu, J., Prior, J. C., Papaioannou, A., Josse, R. G., Towheed, T. E., Davison, K. S., & Sawatzky, R. (2016). Differential item functioning in the SF-36 physical functioning and mental health sub-scales: A population-based investigation in the Canadian multi-centre osteoporosis study. PLoS ONE, 11(3), e0151519. doi: 10.1371/journal.pone.0151519

  •  Lix, L. M., Chan, E. K. H., Sawatzky, R., Sajobi, T. T., Liu, J., Hopman, W., & Mayo, M. (2016). Response shift and disease activity in inflammatory bowel disease. Quality of Life Research, 25(7), 1751-1760. doi: 10.1007/s11136-015-1188-z

  •  Lix, L. M., Sajobi, T. T., Sawatzky, R., Liu, J., Mayo, N. E., Huang, Y., Graff, L. A., Walker, J. R., Ediger, J., Clara, I., Sexton, K., Carr, R., & Bernstein, C. N. (2013). Relative importance measures for reprioritization response shift, Quality of Life Research, 22(3), 695-703. doi: 10.1007/s11136-012-0198-3

  •  Sawatzky, R., Ratner, P. A., Kopec, J. A., & Zumbo, B. D. (2012). Latent variable mixture models: A promising approach for the validation of patient reported outcomes. Quality of Life Research, 21(4), 637-650. doi: 10.1007/s11136-011-9976-6

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This research was undertaken, in part, thanks to funding from the Canadian Institutes of Health Research, the Michael Smith Foundation for Health Research, and the Canada Research Chairs Program in support of Dr. Richard Sawatzky’s Research Chair in Person-Centred Outcomes at Trinity Western University.