References
- Ayele, B. T., Lipkovich, I., Molenberghs, G., Mallinckrodt, C. H. (2014). A multiple imputation based approach to sensitivity analysis and effectiveness assessments in longitudinal clinical trials. Journal of Biopharmaceutical Statistics 24:211–228.
- Carpenter, J., Kenward, M. (2007). Missing data in randomised controlled trials—A practical guide. http://www.hta.nhs.uk/nihrmethodology/reports/1589.pdf.
- Carpenter, J., Roger, J., Kenward, M. (2013). Analysis of longitudinal trials with protocol deviation: A framework for relevant, accessible assumptions, and inference via multiple imputation. Journal of Biopharmaceutical Statistics 23:1352–1371.
- European Medicines Agency. (2010). Guideline on missing data in confirmatory clinical trials. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2010/09/WC500096793.pdf.
- Keller, M., Montgomery, S., Ball, W., Morrison, M., Snavely, D., Liu, G., Hargreaves, R., Hietala, J., Lines, C., Beebe, K., Reines, S. (2006). Lack of efficacy of the substance P (neurokinin receptor) antagonist aprepitant in the treatment of major depressive disorder. Biological Psychiatry 59:216–223.
- Little, R., Yau, L. (1996). Intent-to-treat analysis for longitudinal studies with drop-outs. Biometrics 52:1324–1333.
- Liu, G., Gould, A. L. (2002). Comparison of alternative strategies for analysis of longitudinal trials with dropouts. Journal of Biopharmaceutical Statistics 12:207–226.
- Lu, K. (2013). An analytic method for the placebo-based pattern-mixture model. Statistics in Medicine. doi:10.1002/sim.6008.
- Mallinckrodt, C. H., Lane, P. W., Schnell, D., Peng, Y., Mancuso, J. P. (2008). Recommendations for the primary analysis of continuous endpoints in longitudinal clinical trials. Drug Information Journal 42:305–319.
- Mallinckrodt, C., Roger, J., Chuang-Stein, C., Molenberghs, G., Lane, P.W., Kelly, M.O., Ratitch, B., Xu, L., Gilbert, S., Mehrotra, D., Wolfinger, R., Thijs, H. (2013). Missing data: Turning guidance into action. Statistics in Biopharmaceutical Research. doi:10.1080/19466315.2013.848822.
- Molenberghs, G. Kenward, M. G. (2007). Missing Data in Clinical Studies. Chichester: Wiley.
- National Academy of Sciences. (2010). The prevention and treatment of missing data in clinical trials. In Panel on Handling Missing Data in Clinical Trials. Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.
- O’Kelly, M. Ratitch, B. (2014). Clinical Trials with Missing Data: A Guide for Practitioners. West Sussex: John Wiley & Sons.
- Rubin, D. (1987). Multiple Imputation for Nonresponse in Surveys. New York, NY: Wiley.