Psychometric Evaluation and Calibration of Health-Related Quality of Life Item Banks: Plans for the Patient-Reported Outcomes Measurement Information System (PROMIS)

By B. Reeve, R. Hays, Jakob Bjorner, Karon Cook, Paul K. Crane, Jeanne A. Teresi, D. Thissen, Dennis A. Revicki, David J. Weiss, R. K. Hambleton and 5 more. Medical Care, 2007

1,491 citations recorded by the source corpus.

Subfields: Applied Psychology, Education, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/efbb1fcd4a34b8d013a71828da2378b71521e9dc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Psychology

In Education

In Management Science and Operations Research

Citations in the corpus

Initial Adult Health Item Banks and First Wave Testing of the Patient-Reported Outcomes Measurement Information System (PROMIS™) Network: 2005–2008 (2010, positive): “This article also builds on previous articles that have described the qualitative review process of PROMIS’ item pools [2e4] and the proposed quantitative methods [5] to be used to evaluate the large-scale data collected by PROMIS for item evaluation and calibration for PROMIS item banks.”
Multidimensionality and Structural Coefficient Bias in Structural Equation Modeling (2013, background): “Indeed, some researchers have taken the logic of SEM evaluation and suggested that SEM fit indices be used to evaluate whether item response data are unidimensional enough for IRT modeling (e.g., Cook & Kallen, 2009; Reeve et al., 2007; see also the original work of McDonald & Mok, 1995).”
Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis (2010, methodology): “It is developed as part of a project under the Patient Reported Outcomes Measurement Information System (PROMIS; Reeve et al., 2007), a National Institutes of Health (NIH) roadmap initiative for the development of IRT-based standardized measurement instruments for a variety of patient outcomes frequ”
Practical Guide to Conducting an Item Response Theory Analysis (2014, background): “LD can occur for numerous reasons such as when the wording of two or more item stems or synonyms are used across items that adolescents can’t differentiate between items, thus selecting the same response category across items (see De Ayala, 2009; Reeve et al., 2007).”
Development of Short Forms from the PROMIS Sleep Disturbance and Sleep-Related Impairment Item Banks (2011, methodology): “A more detailed description of the specific PROMIS analytic framework is available elsewhere (see Reeve et al., 2007).”
Using psychometric techniques to improve the Balance Evaluation System’s Test: the mini-BESTest (2010, neutral): “whether items are measuring one underlying dimension or several separate dimensions, is one of the key requisites for test analysis and must be verified before applying Rasch models (13).”
Evaluation of Item Candidates: The PROMIS Qualitative Item Review (2007, methodology): “PROMIS investigators used the following criteria to remove items from consideration: (1) item content was inconsistent with the domain definition; (2) an item was semantically redundant with a previous item; (3) the item content was too narrow to have universal applicability; (4) the stem of the ite”
Development of A Promis Item Bank to Measure Pain Interference (2010, methodology): “, because of large number of items) alternative standards based on exploratory factor analysis (EFA) results were suggested [42].”
Development and assessment of a composite score for memory in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (2012, background): “We compared these candidate secondary domain structures on the basis of published desirable thresholds for the fit statistics (Reeve et al. 2007).”
Development and validation of patient-reported outcome measures for sleep disturbance and sleep-related impairments. (2010, methodology): “Although absolute Q3 values larger than 0.30 are often used to identify local dependence,66 the nature of items banks, such as sleep disturbance and SRI, is expected to produce more locally dependent pairs and clusters67 of items than are other types of item banks, such as cognitive tests.”