Does Jasp have Polynomial Regression?

Comments

• vandenman

  January 12

  There is no good support for polynomial regression yet, but you could use computed columns to manually create variables raised to a power and then include those in the analyses. This means the polynomials are not orthogonal, but if the order is not too large that should be okay.

  I've opened a pull request so that this can at least be done with orthogonal polynomials (see https://github.com/jasp-stats/jasp-desktop/pull/5388)
• TarandeepKang

  January 12

  Hi Don,

  Thanks very much for your very quick work on adding the poly function. But (and as I said above, I'm very new to this) it seems that to take full advantage of this method we also need the ability to obtain MSE via cross validation, to determine model fit. That seems to be the way to determine which order of polynomial is most appropriate to the data in question? If so, do you want me to open another feature request for these to be integrated into their own analysis?
• vandenman

  January 12

  That's a good point. But how exactly that is implemented is specific to the method that is used. For example, in Bayesian linear regression, we automatically account for model complexity. In the frequentist counterpart, however, we would indeed need additional functionality to determine the order of the polynomial.
• TarandeepKang

  January 12

  Ah, yes, I hadn't even considered the Bayesian option (but of course it can use polynomials!) Anyway, since you obviously have a better grasp of this can I do, I won't make the extra request on github. Super save you a job, then I'm glad to.