Literature DB >> 12748405

Developing an initial physical function item bank from existing sources.

Rita K Bode1, David Cella, Jin-shei Lai, Allen W Heinemann.   

Abstract

The objective of this article is to illustrate incremental item banking using health-related quality of life data collected from two samples of patients receiving cancer treatment. The kinds of decisions one faces in establishing an item bank for computerized adaptive testing are also illustrated. Pre-calibration procedures include: identifying common items across databases; creating a new database with data from each pool; reverse-scoring "negative" items; identifying rating scales used in items; identifying pivot points in each rating scale; pivot anchoring items at comparable rating scale categories; and identifying items in each instrument that measure the construct of interest. A series of calibrations were conducted in which a small proportion of new items were added to the common core and misfitting items were identified and deleted until an initial item bank has been developed.

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Year:  2003        PMID: 12748405

Source DB:  PubMed          Journal:  J Appl Meas        ISSN: 1529-7713


  5 in total

1.  The future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment.

Authors:  David Cella; Richard Gershon; Jin-Shei Lai; Seung Choi
Journal:  Qual Life Res       Date:  2007-03-31       Impact factor: 4.147

2.  Measuring participation: the Patient-Reported Outcomes Measurement Information System experience.

Authors:  Rita K Bode; Elizabeth A Hahn; Robert DeVellis; David Cella
Journal:  Arch Phys Med Rehabil       Date:  2010-09       Impact factor: 3.966

3.  Cross-diagnostic validity in a generic instrument: an example from the Functional Independence Measure in Scandinavia.

Authors:  A Lundgren-Nilsson; A Tennant; G Grimby; K S Sunnerhagen
Journal:  Health Qual Life Outcomes       Date:  2006-08-23       Impact factor: 3.186

4.  A brief assessment of physical functioning for prostate cancer patients.

Authors:  Jin-Shei Lai; Rita Bode; Hwee-Lin Wee; David Eton; David Cella
Journal:  Patient Relat Outcome Meas       Date:  2010-06-18

5.  Rasch fit statistics and sample size considerations for polytomous data.

Authors:  Adam B Smith; Robert Rush; Lesley J Fallowfield; Galina Velikova; Michael Sharpe
Journal:  BMC Med Res Methodol       Date:  2008-05-29       Impact factor: 4.615

  5 in total

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