Reliability and Model Fit

Educational and Psychological Measurement - Tập 76 Số 6 - Trang 976-985 - 2016
Leanne Stanley1, Michael C. Edwards1
1The Ohio State University, Columbus, OH, USA.

Tóm tắt

The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the reliability of scores and the fit of a corresponding measurement model to be either acceptable or unacceptable for a given situation, but these are not the only possible outcomes. This article focuses on situations in which model fit is deemed acceptable, but reliability is not. Data were simulated based on the item characteristics of the PROMIS (Patient Reported Outcomes Measurement Information System) anxiety item bank and analyzed using methods from classical test theory, factor analysis, and item response theory. Analytic techniques from different psychometric traditions were used to illustrate that reliability and model fit are distinct, and that disagreement among indices of reliability and model fit may provide important information bearing on a particular validity argument, independent of the data analytic techniques chosen for a particular research application. We conclude by discussing the important information gleaned from the assessment of reliability and model fit.

Từ khóa


Tài liệu tham khảo

10.1007/BF02294359

American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014, Standards for educational and psychological testing

10.1037/0033-2909.107.2.238

Cai L. (2013). flexMIRT® version 2: Flexible multilevel multidimensional item analysis and test scoring [Computer software]. Chapel Hill, NC: Vector Psychometric Group.

10.1080/15366367.2013.835172

10.1007/BF02310555

10.1080/15366367.2013.835178

10.1037/a0015825

10.1080/10705510903203573

Hallquist M., Wiley J. (2014). MplusAutomation: Automating Mplus model estimation and interpretation (R package version 0.6-3). Retrieved from http://CRAN.R-project.org/package=MplusAutomation

10.1080/10705519909540118

10.1007/s11336-010-9165-5

10.1111/jedm.12000

10.1080/15366367.2013.831680

McDonald R. P., 1999, Test theory: A unified treatment

Messick S., 1989, Educational measurement, 3, 13

Muthén L. K., 1998, Mplus user’s guide, 7

10.1177/1073191111411667

R Core Team. (2015). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org/

10.1037/1040-3590.8.4.350

10.1007/s11336-008-9101-0

Steiger J. H., 1980, Paper presented at the Annual Meeting of the Psychometric Society

10.1007/BF02294363

10.1080/15366367.2013.835205

10.1007/BF02291170

10.1037/1082-989X.12.1.58