Consider survey data from surgeries. Y represents observed surgical quality and is measured post-surgery; X represents perceived surgical difficulty level and is measured pre and post surgery.
It is desired to assess the relationship between Y and X.pre and also Y
on X.delta = X.post - X.pre. However, since X.delta is derived from
X.pre, we know that X.pre and X.delta will be highly correlated. One
option is to attempt to reduce such multicollinearity via centering.
Any thoughts on alternative strategies and pros/cons? This scenario
sounds similar to the commonly discussed scenario of how to handle
change scores via ANCOVA (e.g., Senn 2009, Stat Med) when we have change
scores with respect to Y, but it is different since here we have no
baseline Y and a change score for X.
