Should you adjust for covariates when analyzing data from randomized controlled trials?

FDA draft guidance published this month says you should. In most cases, adjusting for covariates is not necessary. Randomization generally insurers that covariates are balanced across clinical trial arms. Randomization, however, may not always result in perfectly balanced trial arms. In these cases, the FDA notes that covariate adjustment is perfectly acceptable. There are some…

Two‐Stage Residual Inclusion: An Overview

Often times, researchers want to measure the effect of certain interventions in the real-world. Doing this in practice is often difficult.  For instance, consider measuring health outcomes among individuals who visit doctors compared to those who don’t.  Inevitably, individuals who visit doctors will have worse outcomes.  Why?  Are doctors killing patients?   This is clearly a…

Nested g-computation procedure

What is the difference in health care cost when two different treatments are used?  This question is challenging because cumulative health care cost is often censored either by death or lack of continuous enrollment.  Lin (2000) addressed this issue in his 2000 paper (see paper and my blog write-up). The problem with this approach, however,…

Dealing with time-censored cost data

We health economists deal with medical cost data all the time.  One challenge we all face is that the medical cost data is often censored.  The censoring may occur because the patient dies.  If you are using administrative health insurance claims data, censoring may occur because people switch their health plan and leave your sample.…