Are hospital ratings systems transparent? An examination of Consumer Reports and the Leapfrog Hospital Safety Grade.

The health care industry is complex, dynamic, and large. In such uncertain environments where a great deal of revenue is at stake, competition and comparative claims flourish. One such manifestation is hospital ratings systems.

Mean centering, multicollinearity, and moderators in multiple regression: The reconciliation redux.

In this article, we attempt to clarify our statements regarding the effects of mean centering. In a multiple regression with predictors A, B, and A × B (where A × B serves as an interaction term), mean centering A and B prior to computing the product term can clarify the regression coefficients (which is good) and the overall model fit R will remain undisturbed (which is also good).

Mean centering helps alleviate "micro" but not "macro" multicollinearity.

There seems to be confusion among researchers regarding whether it is good practice to center variables at their means prior to calculating a product term to estimate an interaction in a multiple regression model. Many researchers use mean centered variables because they believe it's the thing to do or because reviewers ask them to, without quite understanding why. Adding to the confusion is the fact that there is also a perspective in the literature that mean centering does not reduce multicollinearity.