@article {29,
	title = {Developing tailored instruments: item banking and computerized adaptive assessment},
	journal = {Quality of Life Research},
	volume = {16},
	number = {Suppl 1},
	year = {2007},
	note = {Bjorner, Jakob BueChang, Chih-HungThissen, DavidReeve, Bryce B1R43NS047763-01/NS/United States NINDSAG015815/AG/United States NIAResearch Support, N.I.H., ExtramuralNetherlandsQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitationQual Life Res. 2007;16 Suppl 1:95-108. Epub 2007 Feb 15.},
	pages = {95-108},
	edition = {2007/05/29},
	abstract = {Item banks and Computerized Adaptive Testing (CAT) have the potential to greatly improve the assessment of health outcomes. This review describes the unique features of item banks and CAT and discusses how to develop item banks. In CAT, a computer selects the items from an item bank that are most relevant for and informative about the particular respondent; thus optimizing test relevance and precision. Item response theory (IRT) provides the foundation for selecting the items that are most informative for the particular respondent and for scoring responses on a common metric. The development of an item bank is a multi-stage process that requires a clear definition of the construct to be measured, good items, a careful psychometric analysis of the items, and a clear specification of the final CAT. The psychometric analysis needs to evaluate the assumptions of the IRT model such as unidimensionality and local independence; that the items function the same way in different subgroups of the population; and that there is an adequate fit between the data and the chosen item response models. Also, interpretation guidelines need to be established to help the clinical application of the assessment. Although medical research can draw upon expertise from educational testing in the development of item banks and CAT, the medical field also encounters unique opportunities and challenges.},
	keywords = {*Health Status, *Health Status Indicators, *Mental Health, *Outcome Assessment (Health Care), *Quality of Life, *Questionnaires, *Software, Algorithms, Factor Analysis, Statistical, Humans, Models, Statistical, Psychometrics},
	isbn = {0962-9343 (Print)},
	author = {Bjorner, J. B. and Chang, C-H. and Thissen, D. and Reeve, B. B.}
}
@article {86,
	title = {IRT health outcomes data analysis project: an overview and summary},
	journal = {Quality of Life Research},
	volume = {16},
	number = {Suppl. 1},
	year = {2007},
	note = {Cook, Karon FTeal, Cayla RBjorner, Jakob BCella, DavidChang, Chih-HungCrane, Paul KGibbons, Laura EHays, Ron DMcHorney, Colleen AOcepek-Welikson, KatjaRaczek, Anastasia ETeresi, Jeanne AReeve, Bryce B1U01AR52171-01/AR/United States NIAMSR01 (CA60068)/CA/United States NCIY1-PC-3028-01/PC/United States NCIResearch Support, N.I.H., ExtramuralNetherlandsQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitationQual Life Res. 2007;16 Suppl 1:121-32. Epub 2007 Mar 10.},
	pages = {121-132},
	edition = {2007/03/14},
	abstract = {BACKGROUND: In June 2004, the National Cancer Institute and the Drug Information Association co-sponsored the conference, "Improving the Measurement of Health Outcomes through the Applications of Item Response Theory (IRT) Modeling: Exploration of Item Banks and Computer-Adaptive Assessment." A component of the conference was presentation of a psychometric and content analysis of a secondary dataset. OBJECTIVES: A thorough psychometric and content analysis was conducted of two primary domains within a cancer health-related quality of life (HRQOL) dataset. RESEARCH DESIGN: HRQOL scales were evaluated using factor analysis for categorical data, IRT modeling, and differential item functioning analyses. In addition, computerized adaptive administration of HRQOL item banks was simulated, and various IRT models were applied and compared. SUBJECTS: The original data were collected as part of the NCI-funded Quality of Life Evaluation in Oncology (Q-Score) Project. A total of 1,714 patients with cancer or HIV/AIDS were recruited from 5 clinical sites. MEASURES: Items from 4 HRQOL instruments were evaluated: Cancer Rehabilitation Evaluation System-Short Form, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, Functional Assessment of Cancer Therapy and Medical Outcomes Study Short-Form Health Survey. RESULTS AND CONCLUSIONS: Four lessons learned from the project are discussed: the importance of good developmental item banks, the ambiguity of model fit results, the limits of our knowledge regarding the practical implications of model misfit, and the importance in the measurement of HRQOL of construct definition. With respect to these lessons, areas for future research are suggested. The feasibility of developing item banks for broad definitions of health is discussed.},
	keywords = {*Data Interpretation, Statistical, *Health Status, *Quality of Life, *Questionnaires, *Software, Female, HIV Infections/psychology, Humans, Male, Neoplasms/psychology, Outcome Assessment (Health Care)/*methods, Psychometrics, Stress, Psychological},
	isbn = {0962-9343 (Print)},
	author = {Cook, K. F. and Teal, C. R. and Bjorner, J. B. and Cella, D. and Chang, C-H. and Crane, P. K. and Gibbons, L. E. and Hays, R. D. and McHorney, C. A. and Ocepek-Welikson, K. and Raczek, A. E. and Teresi, J. A. and Reeve, B. B.}
}
@article {328,
	title = {Psychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS)},
	journal = {Medical Care},
	volume = {45},
	number = {5 Suppl 1},
	year = {2007},
	note = {Reeve, Bryce BHays, Ron DBjorner, Jakob BCook, Karon FCrane, Paul KTeresi, Jeanne AThissen, DavidRevicki, Dennis AWeiss, David JHambleton, Ronald KLiu, HonghuGershon, RichardReise, Steven PLai, Jin-sheiCella, DavidPROMIS Cooperative GroupAG015815/AG/United States NIAResearch Support, N.I.H., ExtramuralUnited StatesMedical careMed Care. 2007 May;45(5 Suppl 1):S22-31.},
	month = {May},
	pages = {S22-31},
	edition = {2007/04/20},
	abstract = {BACKGROUND: The construction and evaluation of item banks to measure unidimensional constructs of health-related quality of life (HRQOL) is a fundamental objective of the Patient-Reported Outcomes Measurement Information System (PROMIS) project. OBJECTIVES: Item banks will be used as the foundation for developing short-form instruments and enabling computerized adaptive testing. The PROMIS Steering Committee selected 5 HRQOL domains for initial focus: physical functioning, fatigue, pain, emotional distress, and social role participation. This report provides an overview of the methods used in the PROMIS item analyses and proposed calibration of item banks. ANALYSES: Analyses include evaluation of data quality (eg, logic and range checking, spread of response distribution within an item), descriptive statistics (eg, frequencies, means), item response theory model assumptions (unidimensionality, local independence, monotonicity), model fit, differential item functioning, and item calibration for banking. RECOMMENDATIONS: Summarized are key analytic issues; recommendations are provided for future evaluations of item banks in HRQOL assessment.},
	keywords = {*Health Status, *Information Systems, *Quality of Life, *Self Disclosure, Adolescent, Adult, Aged, Calibration, Databases as Topic, Evaluation Studies as Topic, Female, Humans, Male, Middle Aged, Outcome Assessment (Health Care)/*methods, Psychometrics, Questionnaires/standards, United States},
	isbn = {0025-7079 (Print)},
	author = {Reeve, B. B. and Hays, R. D. and Bjorner, J. B. and Cook, K. F. and Crane, P. K. and Teresi, J. A. and Thissen, D. and Revicki, D. A. and Weiss,  D. J. and Hambleton, R. K. and Liu, H. and Gershon, R. C. and Reise, S. P. and Lai, J. S. and Cella, D.}
}
@article {121,
	title = {Data pooling and analysis to build a preliminary item bank: an example using bowel function in prostate cancer},
	journal = {Evaluation and the Health Professions},
	volume = {28},
	number = {2},
	year = {2005},
	note = {0163-2787 (Print)Journal Article},
	pages = {142-59},
	abstract = {Assessing bowel function (BF) in prostate cancer can help determine therapeutic trade-offs. We determined the components of BF commonly assessed in prostate cancer studies as an initial step in creating an item bank for clinical and research application. We analyzed six archived data sets representing 4,246 men with prostate cancer. Thirty-one items from validated instruments were available for analysis. Items were classified into domains (diarrhea, rectal urgency, pain, bleeding, bother/distress, and other) then subjected to conventional psychometric and item response theory (IRT) analyses. Items fit the IRT model if the ratio between observed and expected item variance was between 0.60 and 1.40. Four of 31 items had inadequate fit in at least one analysis. Poorly fitting items included bleeding (2), rectal urgency (1), and bother/distress (1). A fifth item assessing hemorrhoids was poorly correlated with other items. Our analyses supported four related components of BF: diarrhea, rectal urgency, pain, and bother/distress.},
	keywords = {*Quality of Life, *Questionnaires, Adult, Aged, Data Collection/methods, Humans, Intestine, Large/*physiopathology, Male, Middle Aged, Prostatic Neoplasms/*physiopathology, Psychometrics, Research Support, Non-U.S. Gov{\textquoteright}t, Statistics, Nonparametric},
	author = {Eton, D. T. and Lai, J. S. and Cella, D. and Reeve, B. B. and Talcott, J. A. and Clark, J. A. and McPherson, C. P. and Litwin, M. S. and Moinpour, C. M.}
}
