 *example*( pmin ) is useful. I will use it from now on.
Thanks a lot.

On Jan 3, 2008 2:50 AM, Charles C. Berry <cberry@tajo.ucsd.edu> wrote:

> On Thu, 3 Jan 2008, zhijie zhang wrote:
>
> >  Some developments with confusions. I tried the spline method and dummy
> > variable approach to do it. But their results are very different. See
> > following.
> >
>
> [volumes of output and gratuitous SAS code deleted]
>
>
>
> > Q1: Why are these two methods so different for the results, e.g. the
> > coefficients?
>
>
> For the same reason that Thomas replied to my email suggesting a different
> approach than the one I showed you. viz. The spline basis differs from the
> basis vectors he constructed.
>
> >
> > Q2: The spline method is useful for piecewise linear functions, e.g.
> > bs(distance_trans,degree=1,knots=c(13,25)),
> > but how should i do if i want to fit a linear function for the case the
> > distance_trans<13,and quadratic curve when distance_trans>=13?
> > "bs(distance_trans,degree=c(1,2),knots=13)" cannot works. And even for
> more
> > than three parts. <13,13~25, >25.
> >
>
> Whew! My response would be "don't go there". Fit a richer basis than you
> need and use penalization to damp out unneeded variation in the fit. Or
> use GAMs.
>
> But if you feel you must, you can construct things like
>
>        bs( pmax( 13, pmin( 25 , x ) )
>
>
> > Q3:"fit <- glm( y ~ pmax(x,20)+pmin(x,20), family=binomial)" is good.
> But if
> > i divide x into three or more parts, how should i specify it in this
> way?
> >
>
> As above.
>
> > Hope somone can help.Thanks a lot.
> >
>
> You can help youself a lot by taking a few minutes to learn to do in R
> what you did in SAS. Reading the help pages AND running the examples is
> often illuminating. For example,
>
>        example( pmin )
>
> should give you some helpful hints.
>
> HTH,
>
> Chuck
>
>
> >
> >
> > On Jan 2, 2008 11:58 PM, Thomas Lumley <tlumley@u.washington.edu> wrote:
> >
> >> On Tue, 1 Jan 2008, Charles C. Berry wrote:
> >>> On Tue, 1 Jan 2008, zhijie zhang wrote:
> >>>
> >>>> Dear all,
> >>>>  I have two variables, y and x. It seems that the relationship
> between
> >> them
> >>>> is Piecewise Linear Functions. The cutpoint is 20. That is, when
> x<20,
> >> there
> >>>> is a linear relationship between y and x; while x>=20, there is
> another
> >>>> different linear relationship between them.
> >>>> How can i specify their relationships in R correctly?
> >>>> # glm(y~I(x<20)+I(x>=20),family = binomial, data = point)  something
> >> like
> >>>> this?
> >>>
> >>> Try this:
> >>>
> >>>> library(splines)
> >>>> fit <- glm( y ~ bs( x, deg=1, knots=20 ), family=binomial)
> >>>
> >>
> >> In the linear case I would actually argue that there is a benefit from
> >> constructing the spline basis by hand, so that you know what the
> >> coefficients mean. (For quadratic and higher order splines I agree that
> >> pre-existing code for the B-spline basis makes a lot more sense).
> >>
> >> For example, in
> >>   fit <- glm( y ~ pmax(x,20)+pmin(x,20), family=binomial)
> >> the coefficients are the slope when is < 20 and the slope when x>20.
> >>
> >>        -thomas
> >>
> >>
> >> Thomas Lumley                   Assoc. Professor, Biostatistics
> >> tlumley@u.washington.edu        University of Washington, Seattle
> >>
> >
> >
> >
> > --
> > With Kind Regards,
> >
> > oooO:::::::::
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> >
> [***********************************************************************]
> > Zhi Jie,Zhang ,PHD
> > Tel:+86-21-54237149
> > Dept. of Epidemiology,School of Public Health,Fudan University
> > Address:No. 138 Yi Xue Yuan Road,Shanghai,China
> > Postcode:200032
> > Email:epistat@gmail.com
> > Website: www.statABC.com <http://www.statabc.com/>
> >
> [***********************************************************************]
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> >
>
>  Charles C. Berry                            (858) 534-2098
>                                             Dept of Family/Preventive
> Medicine
> E mailto:cberry@tajo.ucsd.edu               UC San Diego
> http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901
>
>
>


-- 
With Kind Regards,

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[***********************************************************************]
Zhi Jie,Zhang ,PHD
Tel:+86-21-54237149
Dept. of Epidemiology,School of Public Health,Fudan University
Address:No. 138 Yi Xue Yuan Road,Shanghai,China
Postcode:200032
Email:epistat@gmail.com
Website: www.statABC.com
[***********************************************************************]
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