References
- Allaire, J. J., Horner, J., Marti, V., & Porte, N. (2015). Markdown: ‘Markdown’ rendering for R. Retrieved from https://CRAN.R-project.org/package=markdown
- Anthoine, E., Moret, L., Regnault, A., Sébille, V., & Hardouin, J.-B. (2014). Sample size used to validate a scale: A review of publications on newly-developed patient reported outcomes measures. Health and Quality of Life Outcomes, 12. https://doi.org/10.1186/s12955-014-0176-2
- Ark, L. A. v. d. (2007). Mokken scale analysis in R. Journal of Statistical Software, 20(11), 1–19.
- Baker, F. B., & Kim, S.-H. (2017). The basics of item response theory using R. Springer International Publishing.
- Bartholomew, D. J. (1998). Scaling unobservable constructs in social science. Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(1), 1–13. https://doi.org/10.1111/1467-9876.00094
- Bond, T., & Fox, C. M. (2015). Applying the Rasch model: Fundamental measurement in the human sciences (3rd ed.). New York, NY: Routledge.
- Borsboom, D. (2005). Measuring the mind: Conceptual issues in contemporary psychometrics. Cambridge, UK: Cambridge University Press.
- Borsboom, D. (2008). Latent variable theory. Measurement: Interdisciplinary Research and Perspectives, 6(1–2), 25–53. https://doi.org/10.1080/15366360802035497
- Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry: Official Journal of the World Psychiatric Association (WPA), 16(1), 5–13. https://doi.org/10.1002/wps.20375
- Borsboom, D., Rhemtulla, M., Cramer, A. O. J., van der Maas, H. L. J., Scheffer, M., & Dolan, C. V. (2016). Kinds versus continua: A review of psychometric approaches to uncover the structure of psychiatric constructs. Psychological Medicine, 46(08), 1567–1579. https://doi.org/10.1017/S0033291715001944
- Broadbent, E., Petrie, K. J., Main, J., & Weinman, J. (2006). The brief illness perception questionnaire. Journal of Psychosomatic Research, 60(6), 631–637. https://doi.org/10.1016/j.jpsychores.2005.10.020
- Cappelleri, J. C., Jason Lundy, J., & Hays, R. D. (2014). Overview of classical test theory and item response theory for the quantitative assessment of items in developing patient-reported outcomes measures. Clinical Therapeutics, 36(5), 648–662. https://doi.org/10.1016/j.clinthera.2014.04.006
- Cella, D., Gershon, R., Lai, J.-S., & Choi, S. (2007). The future of outcomes measurement: Item banking, tailored short-forms, and computerized adaptive assessment. Quality of Life Research, 16(1), 133–141. https://doi.org/10.1007/s11136-007-9204-6
- Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., … PROMIS Cooperative Group. (2010). The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194. https://doi.org/10.1016/j.jclinepi.2010.04.011
- Chalmers, R. P. (2012). Mirt: A multidimensional item response theory package for the R environment. Journal of Statistical Software. https://doi.org/10.18637/jss.v048.i06
- Chan, E. H. (2014). Standards and guidelines for validation practices: Development and evaluation of measurement instruments. In Validity and validation in social, behavioral, and health sciences (pp. 9–24). New York, NY: Springer International Publishing.
- Chen, W.-H., Lenderking, W., Jin, Y., Wyrwich, K. W., Gelhorn, H., & Revicki, D. A. (2014). Is Rasch model analysis applicable in small sample size pilot studies for assessing item characteristics? An example using PROMIS pain behavior item bank data. Quality of Life Research, 23(2), 485–493. https://doi.org/10.1007/s11136-013-0487-5
- Clatworthy, J., Buick, D., Hankins, M., Weinman, J., & Horne, R. (2005). The use and reporting of cluster analysis in health psychology: A review. British Journal of Health Psychology, 10(3), 329–358. https://doi.org/10.1348/135910705X25697
- Cortina, J. M. (1993). What Is coefficient alpha?: An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104. https://doi.org/10.1037/0021-9010.78.1.98
- Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. J. (2015). State of the art personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality, 54, 13–29. https://doi.org/10.1016/j.jrp.2014.07.003
- Crutzen, R., & Peters, G.-J. Y. (2017). Scale quality: Alpha is an inadequate estimate and factor-analytic evidence is needed first of all. Health Psychology Review, 11(3), 242–247. https://doi.org/10.1080/17437199.2015.1124240
- Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399–412. https://doi.org/10.1111/bjop.12046
- Epskamp, S., Borsboom, D., & Fried, E. I. (2017). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 1–18. https://doi.org/10.3758/s13428-017-0862-1
- Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis. Chichester, UK: John Wiley & Sons.
- Flake, J. K., Pek, J., & Hehman, E. (2017). Construct validation in social and personality research: Current practice and recommendations. Social Psychological and Personality Science, 1948550617693063. https://doi.org/10.1177/1948550617693063
- Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286–299.
- Fok, C. C. T., & Henry, D. (2015). Increasing the sensitivity of measures to change. Prevention Science : The Official Journal of the Society for Prevention Research, 16(7), 978–986. https://doi.org/10.1007/s11121-015-0545-z
- Friedman, C., Rubin, J., Brown, J., Buntin, M., Corn, M., Etheredge, L., … Van Houweling, D. (2015). Toward a science of learning systems: A research agenda for the high-functioning learning health system. Journal of the American Medical Informatics Association, 22(1), 43–50. https://doi.org/10.1136/amiajnl-2014-002977
- Fries, J. F., Krishnan, E., Rose, M., Lingala, B., & Bruce, B. (2011). Improved responsiveness and reduced sample size requirements of PROMIS physical function scales with item response theory. Arthritis Research & Therapy, 13, R147. https://doi.org/10.1186/ar3461
- Frost, M. H., Reeve, B. B., Liepa, A. M., Stauffer, J. W., & Hays, R. D. (2007). What Is sufficient evidence for the reliability and validity of patient-reported outcome measures? Value in Health, 10, S94–S105. https://doi.org/10.1111/j.1524-4733.2007.00272.x
- Gandrud, C. (2013). Reproducible research with R and R studio. Boca Raton, FL: CRC Press.
- Graham, J. M. (2006). Congeneric and (essentially) Tau-equivalent estimates of score reliability: What they are and how to use them. Educational and Psychological Measurement, 66(6), 930–944. https://doi.org/10.1177/0013164406288165
- Hamilton, K., Marques, M. M., & Johnson, B. T. (2017). Advanced analytic and statistical methods in health psychology. Health Psychology Review, 11(3), 217–221. https://doi.org/10.1080/17437199.2017.1348905
- Hays, R. D., Morales, L. S., & Reise, S. P. (2000). Item response theory and health outcomes measurement in the 21st century. Medical Care, 38(9 Suppl), II28–II42.
- Hemker, B. T., Sijtsma, K., & Molenaar, I. W. (1995). Selection of unidimensional scales from a multidimensional item bank in the Polytomous Mokken I RT model. Applied Psychological Measurement, 19(4), 337–352. https://doi.org/10.1177/014662169501900404
- Hobart, J., & Cano, S. (2009). Improving the evaluation of therapeutic interventions in multiple sclerosis: The role of new psychometric methods. Health Technology Assessment (Winchester, England), 13(12), iii, ix–x, 1-177. https://doi.org/10.3310/hta13120
- Hogan, T. P., & Agnello, J. (2004). An empirical study of reporting practices concerning measurement validity. Educational and Psychological Measurement, 64(5), 802–812. https://doi.org/10.1177/0013164404264120
- Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
- Hutcheon, J. A., Chiolero, A., & Hanley, J. A. (2010). Random measurement error and regression dilution bias. BMJ, 340, c2289. https://doi.org/10.1136/bmj.c2289
- Jackson, D. L., Gillaspy, J. A., & Purc-Stephenson, R. (2009). Reporting practices in confirmatory factor analysis: An overview and some recommendations. Psychological Methods, 14(1), 6–23. https://doi.org/10.1037/a0014694
- Jensen, M. P., Strom, S. E., Turner, J. A., & Romano, J. M. (1992). Validity of the sickness impact profile Roland scale as a measure of dysfunction in chronic pain patients. Pain, 50(2), 157–162.
- Kamata, A., & Bauer, D. J. (2008). A note on the relation between factor analytic and item response theory models. Structural Equation Modeling: A Multidisciplinary Journal, 15(1), 136–153. https://doi.org/10.1080/10705510701758406
- Kelley, K., & Cheng, Y. (2012). Estimation of and confidence interval formation for reliability coefficients of homogeneous measurement instruments. Methodology, 8(2), 39–50. https://doi.org/10.1027/1614-2241/a000036
- Leisch, F. (2002). Sweave: Dynamic generation of statistical reports using literate data analysis. In W. Härdle, & B. Rönz (Eds.), Compstat 2002 — proceedings in computational statistics (pp. 575–580). Heidelberg: Physica Verlag. Retrieved from http://www.stat.uni-muenchen.de/ leisch/Sweave
- Li, C.-H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavior Research Methods, 48(3), 936–949. https://doi.org/10.3758/s13428-015-0619-7
- Linacre, J. M. (1994). Sample size and item calibration or person measure stability. Rasch Measurement Transactions, 7(4), 328. https://www.rasch.org/rmt/rmt74m.htm
- MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4, 84–99. https://doi.org/10.1037/1082-989X.4.1.84
- Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., & Hornik, K. (2017). Cluster: Cluster analysis basics and extensions.
- Mair, P., & Hatzinger, R. (2007). Extended Rasch modeling: The eRm package for the application of IRT models in R. Journal of Statistical Software, 20(9). Retrieved from https://www.jstatsoft.org/article/view/v020i09
- Marshall, M., Lockwood, A., Bradley, C., Adams, C., Joy, C., & Fenton, M. (2000). Unpublished rating scales: A major source of bias in randomised controlled trials of treatments for schizophrenia. The British Journal of Psychiatry, 176(3), 249–252. https://doi.org/10.1192/bjp.176.3.249
- McHorney, C. A., & Tarlov, A. R. (1995). Individual-patient monitoring in clinical practice: Are available health status surveys adequate? Quality of Life Research, 4(4), 293–307. https://doi.org/10.1007/BF01593882
- Meijer, R. R., & Baneke, J. J. (2004). Analyzing psychopathology items: A case for nonparametric item response theory modeling. Psychological Methods, 9(3), 354–368. https://doi.org/10.1037/1082-989X.9.3.354
- Meijer, R. R., Niessen, A. S. M., & Tendeiro, J. N. (2016). A practical guide to check the consistency of item response patterns in clinical research through person-Fit statistics examples and a computer program. Assessment, 23(1), 52–62. https://doi.org/10.1177/1073191115577800
- Melzack, R. (1987). The short-form McGill pain questionnaire. Pain, 30(2), 191–197. https://doi.org/10.1016/0304-3959(87)91074-8
- Mokkink, L. B., Terwee, C. B., Patrick, D. L., Alonso, J., Stratford, P. W., Knol, D. L., … Vet, H. C. W. d. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: An international Delphi study. Quality of Life Research, 19(4), 539–549. https://doi.org/10.1007/s11136-010-9606-8
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York, NY, US: McGraw-Hill, Inc.
- Peters, G.-J. Y., Dima, A. L., Plass, A. M., Crutzen, R., Gibbons, C., & Doyle, F. (2016). Measurement in health psychology: Combining theory, qualitative, and quantitative methods to do it right: Methods in health psychology symposium VI. The European Health Psychologist, 18(6), 235–246.
- Rabin, R., & Charro, F. d. (2001). EQ-SD: A measure of health status from the EuroQol group. Annals of Medicine, 33(5), 337–343. https://doi.org/10.3109/07853890109002087
- R Core Team. (2013). R: A language and environment for statistical computing. Vienna: Austria. Retrieved from http://www.R-project.org
- Reeve, B. B., Wyrwich, K. W., Wu, A. W., Velikova, G., Terwee, C. B., Snyder, C. F., … Butt, Z. (2013). ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research. Quality of Life Research, 22(8), 1889–1905. https://doi.org/10.1007/s11136-012-0344-y
- Reise, S. P., Ainsworth, A. T., & Haviland, M. G. (2005). Item response theory fundamentals, applications, and promise in psychological research. Current Directions in Psychological Science, 14(2), 95–101. https://doi.org/10.1111/j.0963-7214.2005.00342.x
- Revelle, W. (2017). Psych: Procedures for psychological, psychometric, and personality research. Evanston, IL: Northwestern University. Retrieved from https://CRAN.R-project.org/package=psych
- Revelle, W., & Zinbarg, R. E. (2009). Coefficients alpha, beta, omega, and the glb: Comments on sijtsma. Psychometrika, 74(1), 145. https://doi.org/10.1007/s11336-008-9102-z
- Rizopoulos, D. (2007). Ltm: An R package for latent variable modeling and item response analysis. Journal of Statistical Software, 17(5). https://doi.org/10.18637/jss.v017.i05
- Roland, M., & Morris, R. (1983). A study of the natural history of back pain. Part I: Development of a reliable and sensitive measure of disability in low-back pain. Spine, 8(2), 141–144.
- Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36.
- Sawatzky, R., Chan, E. K. H., Zumbo, B. D., Ahmed, S., Bartlett, S. J., Bingham, C. O., … Lix, L. M. (2016). Modern perspectives of measurement validation emphasize justification of inferences based on patient-reported outcome scores: Seventh paper in a series on patient reported outcomes. Journal of Clinical Epidemiology. https://doi.org/10.1016/j.jclinepi.2016.12.002
- Schmitt, T. A. (2011). Current methodological considerations in exploratory and confirmatory factor analysis. Journal of Psychoeducational Assessment, 29(4), 304–321. https://doi.org/10.1177/0734282911406653
- Schuur, W. H. v. (2003). Mokken scale analysis: Between the Guttman scale and parametric item response theory. Political Analysis, 11(2), 139–163. https://doi.org/10.1093/pan/mpg002
- Sijtsma, K. (2009). On the Use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107. https://doi.org/10.1007/s11336-008-9101-0
- Sijtsma, K., & Hemker, B. T. (1998). Nonparametric polytomous IRT models for invariant item ordering, with results for parametric models. Psychometrika, 63(2), 183–200. https://doi.org/10.1007/BF02294774
- Sijtsma, K., & Molenaar, I. W. (2002). Introduction to nonparametric item response theory. Thousand Oaks, CA: SAGE.
- Singh, J. (2004). Tackling measurement problems with item response theory. Journal of Business Research, 57(2), 184–208. https://doi.org/10.1016/S0148-2963(01)00302-2
- Skevington, S. M., Lotfy, M., & O’Connell, K. A. (2004). The World Health Organization’s WHOQOL-BREF quality of life assessment: Psychometric properties and results of the international field trial. A report from the WHOQOL group. Quality of Life Research, 13(2), 299–310. https://doi.org/10.1023/B:QURE.0000018486.91360.00
- Stochl, J., Jones, P. B., & Croudace, T. J. (2012). Mokken scale analysis of mental health and well-being questionnaire item responses: A non-parametric IRT method in empirical research for applied health researchers. BMC Medical Research Methodology, 12, 74. https://doi.org/10.1186/1471-2288-12-74
- Straat, J. H., van der Ark, L. A., & Sijtsma, K. (2014). Minimum sample size requirements for Mokken scale analysis. Educational and Psychological Measurement, 74(5), 809–822. https://doi.org/10.1177/0013164414529793
- Stroud, M. W., McKnight, P. E., & Jensen, M. P. (2004). Assessment of self-reported physical activity in patients with chronic pain: Development of an abbreviated roland-morris disability scale. The Journal of Pain, 5(5), 257–263. https://doi.org/10.1016/j.jpain.2004.04.002
- Torfs, P., & Brauer, C. (2014, March 3). A (very) short introduction to R. Retrieved from https://cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-Intro.pdf
- Watson, R., van der Ark, L. A., Lin, L.-C., Fieo, R., Deary, I. J., & Meijer, R. R. (2012). Item response theory: How Mokken scaling can be used in clinical practice. Journal of Clinical Nursing, 21(19pt20), 2736–2746. https://doi.org/10.1111/j.1365-2702.2011.03893.x