Causality and the Cox Regression Model

Literature Cited

1. Aalen OO. 1989. A linear regression model for the analysis of life times. Stat. Med. 8:907–25
   [Google Scholar]
2. Aalen OO, Cook RJ, Røysland K. 2015. Does Cox analysis of a randomized survival study yield a causal treatment effect?. Lifetime Data Anal. 21:4579–93
   [Google Scholar]
3. Andersen PK, Borgan Ø, Gill RD, Keiding N. 1993. Statistical Models Based on Counting Processes New York: Springer
4. Andersen PK, Perme MP, van Houwelingen HC, Cook RJ, Joly P et al. 2021. Analysis of time-to-event for observational studies: guidance to the use of intensity models. Stat. Med. 40:1185–211
   [Google Scholar]
5. Bartlett JW, Morris TP, Stensrud MJ, Daniel RM, Vansteelandt SK, Burman CF. 2020. The hazards of period specific and weighted hazard ratios. Stat. Biopharm. Res. 12:4518–19
   [Google Scholar]
6. Benkeser D, Carone M, Laan MJVD, Gilbert PB. 2017. Doubly robust nonparametric inference on the average treatment effect. Biometrika 104:4863–80
   [Google Scholar]
7. Cox DR. 1972. Regression models and life-tables (with discussion). J. R. Stat. Soc. B 34:406–24
   [Google Scholar]
8. Daniel R, Zhang J, Farewell D. 2021. Making apples from oranges: comparing noncollapsible effect estimators and their standard errors after adjustment for different covariate sets. Biom. J. 63:3528–57
   [Google Scholar]
9. De Neve J, Gerds TA. 2020. On the interpretation of the hazard ratio in Cox regression. Biom. J. 62:3742–50
   [Google Scholar]
10. Daz I, Colantuoni E, Hanley DF, Rosenblum M. 2019. Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards. Lifetime Data Anal. 25:3439–68
    [Google Scholar]
11. Hernán MA. 2004. A definition of causal effect for epidemiological research. J. Epidemiol. Community Health 58:4265–71
    [Google Scholar]
12. Hernán MA. 2010. The hazards of hazard ratios. Epidemiology 21:113–15
    [Google Scholar]
13. Hernán MA, Robins JM. 2020. Causal Inference Boca Raton, FL: Chapman & Hall/CRC
14. Hernán MA, Taubman SL. 2008. Does obesity shorten life? The importance of well-defined interventions to answer causal questions. Int. J. Obes. 32:Suppl. 3S8–14
    [Google Scholar]
15. Keiding N. 1998. Selection effects and nonproportional hazards in survival models and models for repeated events Rep., Dep. Biostat., Univ. Copenhagen Copenhagen, Den:.
16. Lederle FA, Kyriakides TC, Stroupe KT, Freischlag JA, Padberg FT et al. 2019. Open versus endovascular repair of abdominal aortic aneurysm. N. Engl. J. Med. 380:222126–35
    [Google Scholar]
17. Lin RS, Lin J, Roychoudhury S, Anderson KM, Hu T et al. 2020a. Alternative analysis methods for time to event endpoints under nonproportional hazards: a comparative analysis. Stat. Biopharm. Res. 12:2187–98
    [Google Scholar]
18. Lin RS, Lin J, Roychoudhury S, Anderson KM, Hu T et al. 2020b. Rejoinder to letter to the editor ``The hazards of period specific and weighted hazard ratios. .'' Stat. Biopharm. Res. 12:4520–21
    [Google Scholar]
19. Lu X, Tsiatis AA 2008. Improving the efficiency of the log-rank test using auxiliary covariates. Biometrika 95:3679–94
    [Google Scholar]
20. Martinussen T, Scheike TH. 2006. Dynamic Regression Models for Survival Data New York: Springer
21. Martinussen T, Vansteelandt S. 2013. On collapsibility and confounding bias in Cox and Aalen regression models. Lifetime Data Anal. 19:3279–96
    [Google Scholar]
22. Martinussen T, Vansteelandt S, Andersen PK. 2020. Subtleties in the interpretation of hazard contrasts. Lifetime Data Anal. 26:4833–55
    [Google Scholar]
23. Nelsen RB. 2006. An Introduction to Copulas New York: Springer
24. Oakes D. 1989. Bivariate survival models induced by frailties. J. Am. Stat. Assoc. 84:406487–93
    [Google Scholar]
25. Ozenne BMH, Scheike TH, Staerk L, Gerds TA. 2020. On the estimation of average treatment effects with right-censored time to event outcome and competing risks. Biom. J. 62:3751–63
    [Google Scholar]
26. Primrose JN, Fox RP, Palmer DH, Malik HZ, Prasad R et al. 2019. Capecitabine compared with observation in resected biliary tract cancer (BILCAP): a randomised, controlled, multicentre, phase 3 study. Lancet Oncol. 20:5663–73
    [Google Scholar]
27. Sjölander A, Dahlqwist E, Zetterqvist J 2016. A note on the noncollapsibility of rate differences and rate ratios. Epidemiology 27:3356–9
    [Google Scholar]
28. Stensrud MJ, Aalen JM, Aalen OO, Valberg M. 2019. Limitations of hazard ratios in clinical trials. Eur. Heart J. 40:171378–83
    [Google Scholar]
29. van der Laan MJ, Rose S. 2011. Targeted Learning New York: Springer
30. van der Laan MJ, Rubin D. 2006. Targeted maximum likelihood learning. Int. J. Biostat. 2:111
    [Google Scholar]
31. van der Vaart AW. 1998. Asymptotic Statistics Cambridge, UK: Cambridge Univ. Press
32. Vansteelandt S, Martinussen T, Tchetgen Tchetgen EJ. 2014. On adjustment for auxiliary covariates in additive hazard models for the analysis of randomized experiments. Biometrika 101:1237–44
    [Google Scholar]