Jonathan Bartlett

Causal interpretation of the hazard ratio from RCTs when proportional hazards holds

February 10, 2018February 6, 2018 by Jonathan Bartlett

In 2015 I wrote a post about the causal interpretation of hazard ratios estimated in randomised trials, following a paper by Aalen and colleagues. One of the arguments made in that paper was that the hazard ratio does not have a valid interpretation as a causal effect in this setting, even when the proportional hazards assumption holds:

This makes it unclear what the hazard ratio computed for a randomized survival study really means. Note, that this has nothing to do with the fit of the Cox model. The model may fit perfectly in the marginal case with X as the only covariate, but the present problem remains.

With recent discussions on estimands in light of the estimand addendum to ICH E9, I have been thinking more on the argument/claim by Aalen et al.

smcfcs – non-linear relationships between covariates

February 4, 2018 by Jonathan Bartlett

I was recently asked about whether smcfcs, my R and Stata packages for multiple imputation of covariates, can accommodate non-linear relationships between covariates. The answer is yes, and in this post I’ll illustrate how this can be done.

Maximum likelihood multiple imputation

December 16, 2017December 16, 2017 by Jonathan Bartlett

I just came across a very interesting draft paper on arXiv by Paul von Hippel on ‘maximum likelihood multiple imputation’. von Hippel has made many important contributions to the multiple imputation (MI) literature, including the paper which advocated that one ‘transform then impute’ when one has interaction or non-linear terms in the substantive model of interest. The present paper on maximum likelihood multiple imputation is in its seventh draft on arXiv, the first being released back in 2012. I haven’t read every detail of the paper, but it looks to me to be another thought provoking and potentially practice changing paper. This post will not attempt by any means to cover all of the important points made in the paper, but will just highlight a few.