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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Modelling Relative Risks with -fracpoly- |

Date |
Wed, 20 Mar 2013 16:40:38 +0000 |

I would look at nonlinear regression texts for bestiaries of functions e.g. http://www.amazon.com/Ecological-Models-Data-Benjamin-Bolker/dp/0691125228 Nick On Wed, Mar 20, 2013 at 4:15 PM, Colin Angus <c.r.angus@sheffield.ac.uk> wrote: > Thanks Nick, > > In this scenario an exposure of 0 is plausible and attainable > (exposure is alcohol consumption, so 0 represents abstention). > Essentially I am trying to pool a variety of RR estimates at different > levels of exposure (all estimated wrt people with 0 exposure) to fit a > dose-response curve. By definition this curve must go through the > point RR=1 at exposure=0, but I can't figure out how to fit a curve > conditional on this. > > Colin Angus > Research Assistant > Health Economics and Decision Science > > School of Health and Related Research (ScHARR) > University of Sheffield > Regent's Court > 30 Regent Street > Sheffield > S1 4DA > > > On 20 March 2013 15:12, Nick Cox <njcoxstata@gmail.com> wrote: >> Sorry, that was too hasty. You said much more than I noticed in a >> brisk reading. >> >> However, forcing through the origin here still seems more problematic >> than usual. >> >> In the easiest applications, (0, 0) is unattainable but a sensible >> limit on physical (biological, economic, ...) grounds. (Mundane >> example: length and area of objects.) In the best applications, >> forcing a function through the origin is also consistent with the data >> say. >> >> Here it seems that RR < 1 and RR > 1 could be something you observe >> even for exposure at or near 0, just as a matter of empirical >> fluctuation. If they are about equally common, your curve should >> reflect that any way. If they aren't equally common, force is not >> nice. >> >> Nick >> >> On Wed, Mar 20, 2013 at 3:03 PM, Nick Cox <njcoxstata@gmail.com> wrote: >>> What is the origin here? >>> >>> Normally something we should all have been able to answer at age 13 or >>> so, but please bear with me. >>> >>> If logRR = 0 then RR = 1. >>> >>> If RR = 0 then logRR is indeterminate. >>> >>> Do you want either limiting behaviour? >>> >>> If so, why? If not, what else? >>> >>> Either way, you could try choosing a set of powers that had the >>> behaviour you want, but that might get in the way of -fracpoly-'s >>> scope for adjusting to the data. >>> >>> Nick >>> >>> On Wed, Mar 20, 2013 at 2:52 PM, Colin Angus <c.r.angus@sheffield.ac.uk> wrote: >>> >>>> I'm using the -fracpoly- command to model the log relative risk of an >>>> event as a function of a single continuous exposure variable, where >>>> the reference category for my relative risk is those with an exposure >>>> of 0 (i.e. my log RR at 0 exposure is 0). So my command is: >>>> >>>> -fracpoly: regress logRR exposure [weight=weight]- >>>> >>>> I cannot see how to force the fitted fractional polynomial function >>>> through the origin. Even if I use the -nocon- command to supress the >>>> constant term, the transformations of the exposure variable mean that >>>> the fitted value at 0 isn't 0. >>>> >>>> Can anybody help me? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Modelling Relative Risks with -fracpoly-***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: Modelling Relative Risks with -fracpoly-***From:*Colin Angus <c.r.angus@sheffield.ac.uk>

**Re: st: Modelling Relative Risks with -fracpoly-***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Modelling Relative Risks with -fracpoly-***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Modelling Relative Risks with -fracpoly-***From:*Colin Angus <c.r.angus@sheffield.ac.uk>

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