A dangerous fact: it is quite possible to talk in a seemingly coherent way about strategies to answer a research question without ever properly specifying what the research question is. The risk is that you end up with the right solution to the wrong problem. The problem is particularly acute for studies where there are risks of “spillovers.”
Consider an observational study looking at the effect of a non-randomly assigned treatment, \(Z\), on an outcome \(Y\). Say you have a pretreatment covariate, \(X\), that is correlated with both \(Z\) and \(Y\). Should you control for \(X\) when you try to assess the effect of \(Z\) on \(Y\)?
Welcome to the
DeclareDesign blog! We have been working on developing the
DeclareDesign family of software packages to let researchers easily generate research designs and assess their properties. Our plan over the next six months is to put up weekly blog posts showing off features of the packages or highlighting the kinds of things you can learn about research design using this approach.