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

Mark J Atkinson¹^,2 and Richard D Lennox³

¹Worldwide Health Outcomes Research, La Jolla Laboratories, Pfizer Inc., San Diego, CA 92121, US

²Health Services Research Center, USCD School of Medicine, La Jolla, CA 92093, US

³Psychometric Technologies, Inc., 402 Millstone Drive, Suite A, Hillsborough, NC 27278, US

author email corresponding author email

Health and Quality of Life Outcomes 2006, 4:65doi:10.1186/1477-7525-4-65


Published:	22 September 2006

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.