Extending basic principles of measurement models to the design and validation of Patient Reported Outcomes

35Citations
Citations of this article
59Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

A recently published article by the Scientific Advisory Committee of the Medical Outcomes Trust presents guidelines for selecting and evaluating health status and health-related quality of life measures used in health outcomes research. In their article, they propose a number of validation and performance criteria with which to evaluate such self-report measures. We provide an alternate, yet complementary, perspective by extending the types of measurement models which are available to the instrument designer. During psychometric development or selection of a Patient Reported Outcome measure it is necessary to determine which, of the five types of measurement models, the measure is based on; 1) a Multiple Effect Indicator model, 2) a Multiple Cause Indicator model, 3) a Single Item Effect Indicator model, 4) a Single Item Cause Indicator model, or 5) a Mixed Multiple Indicator model. Specification of the measurement model has a major influence on decisions about item and scale design, the appropriate application of statistical validation methods, and the suitability of the resulting measure for a particular use in clinical and population-based outcomes research activities. © 2006 Atkinson and Lennox; licensee BioMed Central Ltd.

Cite

CITATION STYLE

APA

Atkinson, M. J., & Lennox, R. D. (2006). Extending basic principles of measurement models to the design and validation of Patient Reported Outcomes. Health and Quality of Life Outcomes, 4. https://doi.org/10.1186/1477-7525-4-65

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free