A New Procedure to Assess When Estimates from the Cumulative Link Model Can Be Interpreted as Differences for Ordinal Scales in Quality of Life Studies

References

• Fayers PM, Machin D. Quality of Life: The Assessment, Analysis and Interpretation of Patient-Reported Outcomes. 2nd ed. Chichester, UK: John Wiley & Sons, Ltd; 2007. doi:10.1002/9780470024522
   Google Scholar
• Arostegui I, Nunez-Anton V, Quintana JM. Statistical approaches to analyse patient-reported outcomes as response variables: an application to health-related quality of life. Stat Methods Med Res. 2012;21(2):189–214. doi:10.1177/096228021037907920858689
   PubMed Web of Science ®Google Scholar
• Alhamzawi R, Ali HTM. Bayesian quantile regression for ordinal longitudinal data. J Appl Stat. 2018;45(5):815–828. doi:10.1080/02664763.2017.1315059
   Web of Science ®Google Scholar
• Alhamzawi R. Bayesian model selection in ordinal quantile regression. Comput Stat Data Anal. 2016;103:68–78. doi:10.1016/j.csda.2016.04.014
   Web of Science ®Google Scholar
• Walters SJ, Campbell MJ, Lall R. Design and analysis of trials with quality of life as an outcome: a practical guide. J Biopharm Stat. 2001;11(3):155–176. doi:10.1081/BIP-10010765511725929
   PubMedGoogle Scholar
• Walters SJ, Campbell MJ. The use of bootstrap methods for analysing health-related quality of life outcomes (particularly the SF-36). Health Qual Life Outcomes. 2004;2:70. doi:10.1186/1477-7525-2-7015588308
   PubMedGoogle Scholar
• Sajobi TT, Zhang Y, Menon BK, et al. Effect size estimates for the ESCAPE trial: proportional odds regression versus other statistical methods. Stroke. 2015;46(7):1800–1805. doi:10.1161/STROKEAHA.115.00932826022639
   PubMed Web of Science ®Google Scholar
• Cappelleri JC, Bushmakin AG. Interpretation of patient-reported outcomes. Stat Methods Med Res. 2014;23(5):460–483. doi:10.1177/096228021347637723427226
   PubMed Web of Science ®Google Scholar
• Crosby RD, Kolotkin RL, Williams GR. Defining clinically meaningful change in health-related quality of life. J Clin Epidemiol. 2003;56(5):395–407. doi:10.1016/s0895-4356(03)00044-112812812
   PubMed Web of Science ®Google Scholar
• McCullagh P, Nelder JA. Generalized Linear Models. 2nd ed. Chapman and Hall/CRC; 1989.
   Google Scholar
• Agresti A. Analysis of Ordinal Categorical Data. 2nd ed. Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2010. doi:10.1002/9780470594001
   Google Scholar
• Winship C, Mare R. Regression models with ordinal variables. Am Sociol Rev. 1984;49(4):512–525. doi:10.2307/2095465
   Web of Science ®Google Scholar
• Liu D, Zhang H. Residuals and diagnostics for ordinal regression models: a surrogate approach. J Am Stat Assoc. 2017. doi:10.1080/01621459.2017.1292915
   Web of Science ®Google Scholar
• Christensen RHB ordinal—regression models for ordinal data. R package version 2018. 4–19; 2018 Available from: http://www.cran.r-project.org/package=ordinal/. Accessed 17, 2021.
   Google Scholar
• Greenwell B, McCarthy A, Boehmke B sure: surrogate residuals for ordinal and general regression models; 2017 Available from: https://cran.r-project.org/package=sure. Accessed 17, 2021.
   Google Scholar
• Greenwell BM, McCarthy AJ, Boehmke BC, Lie D. Residuals and diagnostics for binary and ordinal regression models: an introduction to the sure package. R J. 2018;10(1):381–394. doi:10.32614/RJ-2018-004
   Google Scholar
• Smets EMA, Garssen B, Bonke B, De Haes JCJM. The multidimensional fatigue inventory (MFI) psychometric qualities of an instrument to assess fatigue. J Psychosom Res. 1995;39(3):315–325. doi:10.1016/0022-3999(94)00125-O7636775
   PubMed Web of Science ®Google Scholar
• Krosnick JA, Presser S. Question and Questionnaire Design. In: Handbook of Survey Research. 2nd ed. Emerald Group Publishing Limited; 2010:263–313.
   Google Scholar
• R Core Team. R: a language and environment for statistical computing; 2020 Available from: https://cran.r-project.org. Accessed 17, 2021.
   Google Scholar
• Brundage MD, Wu AW, Rivera YM, Snyder CF. Promoting effective use of patient-reported outcomes in clinical practice: themes from a “Methods Tool kit” paper series. J Clin Epidemiol. 2020;122:153–159. doi:10.1016/j.jclinepi.2020.01.02232061828
   PubMed Web of Science ®Google Scholar
• Jensen RE, Bjorner JB. Applying PRO reference values to communicate clinically relevant information at the point-of-care Medical Care. 2019;57 Suppl 5 Suppl 1:S24–S30. doi:10.1097/MLR.0000000000001113
   Google Scholar
• Cook KF, Cella D, Reeve BB. PRO-bookmarking to estimate clinical thresholds for patient-reported symptoms and function Medical Care. 2019;57 Suppl 5 Suppl 1:S13–S17. doi:10.1097/MLR.0000000000001087
   Google Scholar
• Li J, Humphreys K, Eriksson M, et al. Worse quality of life in young and recently diagnosed breast cancer survivors compared with female survivors of other cancers: A cross-sectional study. Int J Cancer. 2016;139(11):2415–2425. doi:10.1002/ijc.3037027486698
   PubMed Web of Science ®Google Scholar
• Klein D, Mercier M, Abeilard E, et al. Long-term quality of life after breast cancer: a French registry-based controlled study. Breast Cancer Res Treat. 2011;129(1):125–134. doi:10.1007/s10549-011-1408-321340477
   PubMed Web of Science ®Google Scholar
• Hsu T, Ennis M, Hood N, Graham M, Goodwin PJ. Quality of life in long-term breast cancer survivors. J Clin Oncol. 2013;31(28):3540–3548. doi:10.1200/JCO.2012.48.190323980087
   PubMed Web of Science ®Google Scholar
• Nordin Å, Taft C, Lundgren-Nilsson Å, Dencker A. Minimal important differences for fatigue patient reported outcome measures-a systematic review. BMC Med Res Methodol. 2016;16:62. doi:10.1186/s12874-016-0167-627387456
   PubMed Web of Science ®Google Scholar
• Fayers PM, Machin D. Quality of Life : The Assessment, Analysis and Interpretation of Patient-Reported Outcomes. 2nd ed. John Wiley & Sons; 2007.
   Google Scholar
• Alhamzawi R, Mohammad Ali HT. Bayesian single-index quantile regression for ordinal data. Commun Stat Simul Comput. 2020;49(5):1306–1320. doi:10.1080/03610918.2018.1494283
   Web of Science ®Google Scholar
• Muraki E. A generalized partial credit model: application of an EM algorithm. Appl Psychol Meas. 1992;16(2):159–176. doi:10.1177/014662169201600206
   Web of Science ®Google Scholar
• van der Linden WJ, Hambleton RK, eds. Item Response Theory. 1st ed. Springer-Verlag New York; 1997. doi:10.1007/978-1-4757-2691-6
   Google Scholar
• Nguyen TH, Han HR, Kim MT, Chan KS. An introduction to item response theory for patient-reported outcome measurement. Patient. 2014;7(1):23–35. doi:10.1007/s40271-013-0041-024403095
   PubMedGoogle Scholar
• McCullagh P. Regression models for ordinal data. J R Stat Soc Ser B. 1980;42(2):109–142.
   Google Scholar