Abstract
Evaluating the effectiveness of treatment for long-term chronic conditions requires more sensitive measures of quality of life and daily functioning than those treatments for acute care. Unfortunately, most of these measures require some degree of subjective reports and are affected by a number of systematic and unsystematic measurement errors that typically increase the probability of incorrectly declaring the treatment ineffective or indicative of a Type II error. These include method effects, such as social desirability or acquiescence, and structural errors that occur when the items reliably measure something other than what they were intended to measure. This paper explores some potential methods for removing or otherwise controlling random measurement error, assessment artifacts, irrelevant variation in outcome measures, and confounding sources of covariation in a structural equations paradigm. Using examples with some popular measures of quality of life and functioning, the paper also looks at the appropriateness of their use in observational, quasi-, and randomized field experiments.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
