Posts

Is the JAMA opening up their language for causal effects?

causal inference

Randomized controlled trials (RCTs) measure the causal effect of interventions, but results from observational studies should be interpreted as mere associations, right? In…

Wouter van Amsterdam

Partial residual plots with multiply imputed data

r

linear regression

data visualization

In an earlier blog post I show how to plot the dependence of a response variable on covariate, both conditional on other covariates with a partial residual plot In this post…

Wouter van Amsterdam

The need for speed, performing simulation studies in R, JAX and Julia

r

julia

jax

python

simulation studies

Simulation experiments are important when evaluating methods but also for applied work in for example power analyses (e.g. Amsterdam, Harlianto, et al. 2022) or sensitivity…

Wouter van Amsterdam

The difference between intervention and counterfactuals

causal inference

statistics

Sometimes there is confusion about the difference between counterfactual predictions and interventional predictions. According to the ladder of causation introduced by Pearl…

Wouter van Amsterdam

When good predictions lead to bad decisions

causal inference

predictions

A common premise in prediction research for clinical outcomes is that better predictions lead to better (informed) decisions. This causal statement, that the intervention of…

Wouter van Amsterdam

Finding the functional form for multiple linear regression

statistics

simulations

linear regression

A frequent question that comes up when modeling continuous outcomes with multiple linear regression is what the correct functional form for the relationship between the…

Wouter van Amsterdam