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Re: st: Modelling Relative Risks with -fracpoly-

From   Colin Angus <>
Subject   Re: st: Modelling Relative Risks with -fracpoly-
Date   Wed, 20 Mar 2013 16:15:37 +0000

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
S1 4DA

On 20 March 2013 15:12, Nick Cox <> 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 <> 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 <> 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?
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