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I'm looking for some more sophisticated analytical methods for assessing age-at-exposure effects. The literature I'm reading typically polytomizes age into groups, which I'd like to use as a last resort. I'd like to model age-at-exposure as a continuous variable and calc risk per year. It's possible the effects I'm looking at are non-linear. I'd rather not calculate an average slope across age... this would attenuate effects I expect to see.

Let's say I have access to data that are both cross-sectional and longitudinal, but only two time points for the latter right now.

Has anyone come across statistical methods that would serve these purposes?

Thank you.

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  • $\begingroup$ This is a question about moderation, so I've added the interaction tag. You can use moderation techniques easily if you have a randomized exposure or you can estimate the exposure effect at each year with a parametric model. $\endgroup$ – Noah Apr 5 at 18:54
  • $\begingroup$ How is this about moderation? OP only mentions one independent variable. $\endgroup$ – Peter Flom Apr 8 at 12:00
  • $\begingroup$ I've been mulling that comment over for a few days now trying to figure out how my question was interpreted as about moderation...thanks for the validation Peter. $\endgroup$ – user31801 Apr 9 at 16:46
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There are a variety of techniques for modeling nonlinear relationships.

Perhaps the simplest is to use polynomials. That has its problems, especially with extrapolation and interpolation, but does provide a simple solution that is relatively easy to interpret. It is particularly applicable if there is theoretical reason to expect a specific relationship.

Splines are a very flexible set of methods for fitting almost any relationship. There's a huge number of different spline methods, but, from what I've read, the standard seems to be gradually becoming restricted cubic splines.

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    $\begingroup$ For details and examples of restricted cubic splines see my RMS course notes. $\endgroup$ – Frank Harrell Apr 8 at 12:14
  • $\begingroup$ Thanks for this! I'm familiar with modeling polynomials. It's the risk per year/age of exposure that I'd like to produce a series of slopes for. I'm really looking for sensitive/critical periods in childhood/adolescence. $\endgroup$ – user31801 Apr 9 at 16:45
  • $\begingroup$ Splines will surely do better than polynomials for finding critical periods. I know you can let the program find the knots, but I am not sure how well that works. You can also choose knots at various percentiles of the distribution. $\endgroup$ – Peter Flom Apr 10 at 12:18
  • $\begingroup$ Which program are you referencing, @PeterFlom? $\endgroup$ – user31801 Apr 23 at 20:44
  • $\begingroup$ None in particular. I know you can do this in SAS and in R. I would assume you can also do it in other packages. $\endgroup$ – Peter Flom Apr 23 at 20:50

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