Survival distributions in R

My former colleague Devin Incerti has a nice summary of how to implement survival function estimation in R. Not only does he mathematically describe the probability density function (PDF), cumulative density function (CDF), and hazard rates for 8 commonly used parametric survival curves [see table below], he also describes how to implement these using the…

Instrumental variables: Can I use patient level IVs to correct for endogeneity in patient characteristics?

Does a treatment improve patient health?  Does a policy intervention improve quality of life?  Does more education increase income?  These are fundamental questions that are difficult to answer with standard observational approaches.  The reason?  Selection bias.  Patients who are sick take medicine; patients who are sicker may take more medicine.  Thus, one could observe that…

How to choose a Bayesian prior

Bayesian analysis is increasingly common in health economic research.  To apply Bayesian models, however, you need to select a prior distribution.  How do you select your prior?  Andrew Gelman (of the excellent Statistical Modeling, Causal Inference, and Social Science blog) provides some advice on selecting a prior on the stan-dev GitHub website.  I review some…

Marginal Structural Models

So you want to compare two treatments–for instance Treatment A and Treatment B–in order to see which one has largest impact on health outcomes. Sure you could do a randomized controlled trial, but let’s say you don’t have the funding for that. You could use real world data to conduct just such an analysis. Let’s…

Causality: Granger Causality

Earlier this year, I reviewed one definition of causality: the Bradford Hill criteria. Now I move from a medical definition causality to one developed by an economist (in fact, an economist from my alma matter). Granger causality basically identifies a variable as causal if: (i) it occurs the outcome of interest and (ii) including past…

Do pharmaceuticals improve quality of life? A Bayesian answer to the question when there is missing data

Let’s say we are interested in determining whether a particular treatment improves quality of life. Common measures of quality of life include EQ-5D, SF-12, and SF-36, among others. However, a systematic review of 237 randomized controlled trials found that only 43% collected SF-12 or SF-36 measures. If you are measuring a treatment’s effect on quality…