Having a fit: impact of number of items and distribution of data on traditional criteria for assessing IRT's unidimensionality assumption.
Purpose: Confirmatory factor analysis fit criteria typically are used to evaluate the unidimensionality of item banks. This study explored the degree to which the values of these statistics are affected by two characteristics of item banks developed to measure health outcomes: large numbers of items...
| Published in: | Quality of Life Research Vol. 18; no. 4; pp. 447 - 461 |
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| Main Authors: | , , , , , |
| Format: | research Journal Article |
| Published: |
Springer Nature
May2009
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105492181&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105492181 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09629343 GPQ jtl: Quality of Life Research issn: 09629343 maglogo: N pubinfo: dt: May2009 vid: 18 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105492181 105492181 NLM19294529 2010239644 10.1007/s11136-009-9464-4 NLM19294529 PMC2746381 105492181 ppf: 447 ppct: 14 formats: fmt: @attributes: type: P tig: atl: Having a fit: impact of number of items and distribution of data on traditional criteria for assessing IRT's unidimensionality assumption. aug: au: Cook KF Kallen MA Amtmann D Cook, Karon F Kallen, Michael A Amtmann, Dagmar affil: Department of Rehabilitation Medicine, University of Washington, Box 357920, Seattle, WA, 98195-7920, USA sug: subj: Pain Measurement Methods Quality of Life Questionnaires Self-Efficacy Activities of Daily Living Adolescence Adult Aged Aged, 80 and Over Disability Evaluation Factor Analysis Female Male Middle Age Treatment Outcomes Human Adolescent: 13-18 years Adult: 19-44 years Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: Purpose: Confirmatory factor analysis fit criteria typically are used to evaluate the unidimensionality of item banks. This study explored the degree to which the values of these statistics are affected by two characteristics of item banks developed to measure health outcomes: large numbers of items and nonnormal data.Methods: Analyses were conducted on simulated and observed data. Observed data were responses to the Patient-Reported Outcome Measurement Information System (PROMIS) Pain Impact Item Bank. Simulated data fit the graded response model and conformed to a normal distribution or mirrored the distribution of the observed data. Confirmatory factor analyses (CFA), parallel analysis, and bifactor analysis were conducted.Results: CFA fit values were found to be sensitive to data distribution and number of items. In some instances impact of distribution and item number was quite large.Conclusions: We concluded that using traditional cutoffs and standards for CFA fit statistics is not recommended for establishing unidimensionality of item banks. An investigative approach is favored over reliance on published criteria. We found bifactor analysis to be appealing in this regard because it allows evaluation of the relative impact of secondary dimensions. In addition to these methodological conclusions, we judged the items of the PROMIS Pain Impact bank to be sufficiently unidimensional for item response theory (IRT) modeling. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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