08-04-2012 09:43 PM
At r-square = 0.1, your model has essentially no predictive power. If you give some description of the variables and of the way the observations were acquired (sampling/experimental plan) someone might be able to suggest a better statistical model or at least, alternative data exploration methods and modeling approaches.
08-04-2012 10:27 PM
"At r-square = 0.1, your model has essentially no predictive power."
Are you sure? The CMS-HCC model used by CMS to pay private insurance companies has R-square of 0.09. The model my company is using has R-square of 0.1, but it already helped the company save a lot of money.
Variable transformation is one way which possible help improve the model's predictive power. I would like to know what other options I can have without acquiring more variables.
08-04-2012 10:50 PM
It is true that strength of evidence requirements vary a lot across disciplines. - To go beyond regression, you might want to consider the model building techniques provided by data mining tools - PG