Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down at the end of May, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

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

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Thu, 21 Mar 2013 17:44:25 +0000 |

I alerted Patrick Royston to this thread. (Patrick is not a member of Statalist, but one of the progenitors of fractional polynomials.) He wrote: "Sounds to me potentially like a "spike at zero" problem, which occurs when the exposure is semi-continuous (e;g. cigarettes smoked per day) and you wish to model a "probability spike" at zero exposure and a continuous function for positive exposures. The topic -- sometimes cryptically known as the "Robertson problem" due to an early paper on this by said author -- is discussed in our 2008 book (Royston & Sauerbrei, "Multivariable model-building", Wiley, Chichester) and treated in detail in a paper in press with the Biometrical Journal (Becher, Lorenz, Royston, Sauerbrei, 2013). Actually, -fracpoly- has undocumented options -zero- and -catzero- that are designed for this problem. Curiously, similar options are available with -mfp- that are documented. Colin may wish to investigate this avenue. He could indeed use -mfp- instead of -fracpoly- if he wished." Nick On Wed, Mar 20, 2013 at 4:40 PM, Nick Cox <njcoxstata@gmail.com> wrote: > 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/

**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>

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

- Prev by Date:
**Re: st: Alternatives to box plots** - Next by Date:
**RE: st: ordered logistic integration problems** - Previous by thread:
**Re: st: Modelling Relative Risks with -fracpoly-** - Next by thread:
**st: clear estimated coefficient** - Index(es):