[hutennis]

Originally posted on 02/05/2012:

Im just trying to figure out the best way to analyze my model...

Maybe, for starters, you should make sure that you have a model in a first place?

Here is a hint for you.

A successful model must be able to make predictions which will be farther confirmed, under controlled conditions, by statistically significant experimental results.

Any backward looking only “models” are nothing more but a research, collection of data that is used to form a hypothesis.

This hypothesis must be tested by confirmation of a specific prediction by science fair experiment to make sure that your hypothesis is not wrong and your research is not negatively affected and thus rendered useless by confirmation bias, forward bias, hindsight bias, Texas sharpshooter fallacy, data fishing, misunderstanding of the law of large numbers, misusing regression to the mean, gambler’s fallacy, illusion of correlation and who knows how many more different cognitive, logical, statistical and decision-making biases and fallacies.

Any positive results achieved by using research data only (or what great many people erroneously call "my model"), can and should be safely attributed to luck.