Web-Appendix 1 WEB-APPENDIX for “ Comparison of Statistical Approaches Dealing with Immortal Time Bias in Drug Effectiveness Studies ”

[1]  P. Gustafson,et al.  Practice of Epidemiology Marginal Structural Cox Models for Estimating the Association Between β-Interferon Exposure and Disease Progression in a Multiple Sclerosis Cohort , 2014 .

[2]  K. Leffondré,et al.  On the proportional hazards model for occupational and environmental case-control analyses , 2013, BMC Medical Research Methodology.

[3]  P. Gustafson,et al.  Association between use of interferon beta and progression of disability in patients with relapsing-remitting multiple sclerosis. , 2012, JAMA.

[4]  Michal Abrahamowicz,et al.  Comparison of alternative models for linking drug exposure with adverse effects , 2012, Statistics in medicine.

[5]  Catherine Quantin,et al.  Flexible modeling of the effects of continuous prognostic factors in relative survival , 2011, Statistics in medicine.

[6]  D. Richardson,et al.  Flexible modeling of the cumulative effects of time‐dependent exposures on the hazard , 2011, Statistics in medicine.

[7]  K. Rothman,et al.  Exclusion of immortal person‐time , 2008, Pharmacoepidemiology and drug safety.

[8]  S. Suissa.  Practice of Epidemiology Immortal Time Bias in Pharmacoepidemiology , 2008 .

[9]  M. Abrahamowicz,et al.  Joint estimation of time‐dependent and non‐linear effects of continuous covariates on survival , 2007, Statistics in medicine.

[10]  Michal Abrahamowicz,et al.  Marginal and hazard ratio specific random data generation: Applications to semi-parametric bootstrapping , 2002, Stat. Comput..

[11]  Michal Abrahamowicz,et al.  Time-Dependent Hazard Ratio: Modeling and Hypothesis Testing with Application in Lupus Nephritis , 1996 .

[12]  J. Kurtzke.  Rating neurologic impairment in multiple sclerosis , 1983, Neurology.

[13]  David R. Cox,et al.  Regression models and life tables (with discussion , 1972 .