st: meta-regression - fitting quadratics

[Daniel Davis <dhjd2@medschl.cam.ac.uk>]

Dear Statalisters,

I'm wondering how to fit nonlinear meta-regression models.

I'm conducting a literature-based meta-analysis, combining estimates of
prevalence of drug resistance. Each study reports a prevalence and
(within-study) standard errors can be derived. The appropriate approach
for pooling these estimates is to use a random-effects model. One key
covariate is duration exposed to the drug (to which resistance has
developed). Using metareg, I can see how the prevalence estimates vary
as a function of duration. So far so good.

What are the appropriate post-estimation procedures that may (or may
not) point to fitting polynomial quantities? A priori, the relationship
between drug resistance and duration of treatment is *not* likely to be
constant over time, e.g. resistance might emerge more rapidly during the
first year or two, and then the relationship might plateau.

I'd be very grateful for your collective thoughts on how to approach
this.

Many thanks and best wishes,
Daniel Davis

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