1. Yanagida, T., K.D. Kubinger, and D. Rasch, Planning a Study for Testing the Rasch Model given Missing Values due to the use of Test-booklets. J Appl Meas, 2015. 16(4): p. 432-42.
2. Baba, S., et al., Reliability of the SF-36 in Japanese patients with systemic lupus erythematosus and its associations with disease activity and damage: a two-consecutive year prospective study. Lupus, 2018. 27(3): p. 407-416.
3. Janani, K., et al., Health-related quality of life in liver cirrhosis patients using SF-36 and CLDQ questionnaires. Clin Exp Hepatol, 2018. 4(4): p. 232-239.
4. Erez, G., L. Selman, and F.E. Murtagh, Measuring health-related quality of life in patients with conservatively managed stage 5 chronic kidney disease: limitations of the Medical Outcomes Study Short Form 36: SF-36. Qual Life Res, 2016. 25(11): p. 2799-2809.
5. Bunevicius, A., Reliability and validity of the SF-36 Health Survey Questionnaire in patients with brain tumors: a cross-sectional study. Health Qual Life Outcomes, 2017. 15(1): p. 92.
6. Peyre, H., A. Leplege, and J. Coste, Missing data methods for dealing with missing items in quality of life questionnaires. A comparison by simulation of personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques applied to the SF-36 in the French 2003 decennial health survey. Quality of Life Research, 2011. 20(2): p. 287-300.
7. Aaronson, N.K., et al., The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst, 1993. 85(5): p. 365-76.
8. Ware, J.E., Jr. and C.D. Sherbourne, The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care, 1992. 30(6): p. 473-83.
9. Fielding, S., et al., Simple imputation methods were inadequate for missing not at random (MNAR) quality of life data. Health Qual Life Outcomes, 2008. 6: p. 57.
10. Molenberghs, G., et al., Analyzing incomplete longitudinal clinical trial data. Biostatistics, 2004. 5(3): p. 445-64.
11. Shrive, F.M., et al., Dealing with missing data in a multi-question depression scale: a comparison of imputation methods. BMC Med Res Methodol, 2006. 6: p. 57.
12. Springer K. W., H.R.M., An assessment of the construct validity of RyV's Scales of psychological well-being: method, mode, and measurement effects. . Soc. Sci. Res., 2006. 35: p. 1080–1102. .
13. Lawton, M.P. and E.M. Brody, Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist, 1969. 9(3): p. 179-86.
14. M., R., Society and the adolescent self-image. . 1965, Princeton NJ: Princeton University Press.
15. DB, R., Inference and missing data. . Biometrika, 1976. 63: p. 581–92.
16. Little, R., Rubin, DB. , Statistical Analysis with Missing Data. . 2014, Hoboken, NJ, USA: John Wiley & Sons.
17. Gelman, A., Hill, J., Data Analysis Using Regression and Multilevel/Hierarchical Models. 2006, Cambridge, UK: Cambridge University Press.
18. Sande, I., Hot Deck imputation procedures, incomplete data in samples surveys. . 1983, New York: Academic Press. .
19. Rubin, D., Multiple imputation for nonreponse in surveys. 1987, New York: John Wiley and Sons. .
20. To, K.T., R.C. Fry, and D.M. Reif, Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi. BioData Min, 2018. 11: p. 10.
21. Cheng, S.H., et al., A study on the sleep quality of incoming university students. Psychiatry Res, 2012. 197(3): p. 270-4.
22. Stoltzfus, J.C., Logistic regression: a brief primer. Acad Emerg Med, 2011. 18(10): p. 1099-104.
23. Read, S.H., et al., Measuring the Association Between Body Mass Index and All-Cause Mortality in the Presence of Missing Data: Analyses From the Scottish National Diabetes Register. Am J Epidemiol, 2017. 185(8): p. 641-649.
24. S., v.B., Flexible Imputation of Missing Data. . 2012, CRC Press: Taylor & Francis.
25. Donders, A.R., et al., Review: a gentle introduction to imputation of missing values. J Clin Epidemiol, 2006. 59(10): p. 1087-91.