@article {384,
	title = {Overview of quantitative measurement methods. Equivalence, invariance, and differential item functioning in health applications},
	journal = {Medical Care},
	volume = {44},
	number = {11 Suppl 3},
	year = {2006},
	note = {Teresi, Jeanne AAG15294/AG/NIA NIH HHS/United StatesResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov{\textquoteright}tReviewUnited StatesMedical careMed Care. 2006 Nov;44(11 Suppl 3):S39-49.},
	month = {Nov},
	pages = {S39-49},
	edition = {2006/10/25},
	abstract = {BACKGROUND: Reviewed in this article are issues relating to the study of invariance and differential item functioning (DIF). The aim of factor analyses and DIF, in the context of invariance testing, is the examination of group differences in item response conditional on an estimate of disability. Discussed are parameters and statistics that are not invariant and cannot be compared validly in crosscultural studies with varying distributions of disability in contrast to those that can be compared (if the model assumptions are met) because they are produced by models such as linear and nonlinear regression. OBJECTIVES: The purpose of this overview is to provide an integrated approach to the quantitative methods used in this special issue to examine measurement equivalence. The methods include classical test theory (CTT), factor analytic, and parametric and nonparametric approaches to DIF detection. Also included in the quantitative section is a discussion of item banking and computerized adaptive testing (CAT). METHODS: Factorial invariance and the articles discussing this topic are introduced. A brief overview of the DIF methods presented in the quantitative section of the special issue is provided together with a discussion of ways in which DIF analyses and examination of invariance using factor models may be complementary. CONCLUSIONS: Although factor analytic and DIF detection methods share features, they provide unique information and can be viewed as complementary in informing about measurement equivalence.},
	keywords = {*Cross-Cultural Comparison, Data Interpretation, Statistical, Factor Analysis, Statistical, Guidelines as Topic, Humans, Models, Statistical, Psychometrics/*methods, Statistics as Topic/*methods, Statistics, Nonparametric},
	isbn = {0025-7079 (Print)0025-7079 (Linking)},
	author = {Teresi, J. A.}
}
@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.}
}
