Are health care prices falling?
It seems like everything just gets more and more expensive. But are prices for medical care declining? Cutler et al. (1998) found in seminal paper […]
Econometrics
How linear mixed models can help with missing data
What should you do when you want to conduct a cost-effectiveness analysis based on efficacy estimates from clinical trials but the trial has missing data. […]
BAyeSian Interpretation of Estimates (BASIE)
Imagine that you are a policymaker and an academic researcher shows you evidence for a new health intervention that will dramatically improve health outcomes. He […]
What is collider bias?
A paper by Holmberg et al. (2022) in JAMA provides a number of examples of how collider bias can lead to problematic causal inference. The […]
Measuring risk preferences over health states
This is the goal of a paper by Yang et al. (2022) out in Health Economics. They first provide a nice review of the literature […]
F1…and I’m not talking about racing
Most people know what accuracy means. Find out how many guesses you made and how many of those guesses you got correct. In the case […]
Difference-in-Difference or Synthetic Control Method?
When you want to measure the causal impact of an intervention, there are a number of different approaches. Difference in difference (DiD) and the synthetic […]
I have too many control variables…which ones should I include in my regression model?
Supposed you have some data on health care spending for different individuals and you want to know which patient characteristics increase health care spending. While […]
Distributional Cost Effectiveness Analysis: A simple example
I have written previously about the need for distributional cost-effectiveness analysis (DCEA) which would increase the value of treatments who improve the health for individuals […]
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FDA draft guidance published this month says you should.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 […]
What is immortal time bias?
A recent JAMA paper by Yadav and Lewis (2021) provide the answer: Bias from immortal time periods is the error in estimating the association between […]
Use of real-world evidence for regulatory decision-making
How do you evaluate treatment efficacy and safety outside of the clinical trial setting? This is not just a question of academic interest. In last […]
If you have a positive COVID test, how likely is it that you actually have COVID?
[Disclaimer: this post provides the math behind how to answer this question without actually answering the question] If you get a positive test for COVID-19, […]
Did your real-world study follow STROBE guidelines?
Is your observational research study following best practices? Is your methodology transparent? To help answer these questions, the Enhancing the QUAlity and Transparency Of health […]
When (and how) to use population-adjusted indirect comparisons?
Population-adjusted indirect comparisons (PAICs) include both matching-adjusted indirect comparisons (MAICs) and Simulated treatment comparisons (STCs). The key data requirement for these methods is that they […]
What about a cure model?
That is the title of a helpful video from Nicholas Lattimer of University of Sheffield. You can view all his videos here.
Can I use a Cox proportional hazard model to treatment effect?
In many clinical trials, the outcome of interest may be some form of time to event outcome. This could be time until death, time until […]
Estimating survival gains based on clinical trial data
How do you measure the value value of new treatments that improve survival? Clearly one of the key factors for doing so is understanding how […]