My dependent variable fits at least one definition of a time series: "If you take a sequence of equally spaced readings, this is called a time series." Furthermore, there is very strong autocorrelation (near 1) in the dependent variable -- when tested in the order the data is collected. However, I can randomly resort all the data (dependent plus independent variables) so that there is no longer any autocorrelation and this does not affect the predictive ability of the independent variables. So I'm thinking that I am not dealing with a time series. Any thoughts?
Any arguments in favor of using time series analyses? Knowing that I _can_ remove the autocorrelation, can I proceed to perform parametric regression analysis without actually randomly sorting the data and treat this as a non-time-series analysis? TIA Steve . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
