Granted, a model that’s too simple—for instance, the straight line of the one-factor formula—can fail to capture the essential pattern in the data. If the truth looks like a curve, no straight line can ever get it right. On the other hand, a model that’s too complicated, such as our nine-factor model here, becomes oversensitive to the particular data points that we happened to observe. As a consequence, precisely because it is tuned so finely to that specific data set, the solutions it produces are highly variable. If the study were repeated with different people, producing slight variations
...more
