[R] lm help: using lm when one point is known (not y intercept)

[Martin Maechler]

>>>>> "JohnF" == John Fox <jfox at mcmaster.ca>
>>>>>     on Sat, 27 Nov 2004 23:49:08 -0500 writes:

    JohnF> Dear Seth,

    JohnF> You don't say which variable is the explanatory
    JohnF> variable and which is the response, but assuming that
    JohnF> prob is to be regressed on effect, you can fit
    JohnF> lm(prob - 50 ~ I(effect + 37.25) - 1). That is you
    JohnF> can shift the point through which the regression is
    JohnF> to go to the origin and then force the regression
    JohnF> through the origin.

    JohnF> I hope this helps,
yes, nice!

Even a bit more useful {though slightly uglier} is to use offset():

     mfit <- lm(prob ~ offset(50+ 0*effect) + I(effect + 37.25) - 1)

such that e.g. predict(mfit, ...) will still predict 'prob'

Note however that for both solutions, the regression abline()
will look wrong {and I hoped it would also be ok when using offset()},
plot(prob ~ effect)  ; abline(mfit)

Martin


    JohnF> John

    JohnF> --------------------------------
    JohnF> John Fox
    JohnF> Department of Sociology
    JohnF> McMaster University
    JohnF> Hamilton, Ontario
    JohnF> Canada L8S 4M4
    JohnF> 905-525-9140x23604
    JohnF> http://socserv.mcmaster.ca/jfox 
    JohnF> -------------------------------- 

    >> -----Original Message-----
    >> To: r-help at stat.math.ethz.ch
    >> Subject: [R] lm help: using lm when one point is known (not y intercept)
    >> 
    >> Hello-
    >> 
    >> My question is a short one.  How can I specify a single point 
    >> which through the fitted linear model has to go through?  To 
    >> illustrate my problem, the fit to following data must go 
    >> through the point (-37.25(effect), 50(prob)).  Note: you can 
    >> ignore the label column.
    >> 
    >> Effect      Prob Label
    >> 
    >> 1 -1143.75  7.142857     L
    >> 2  -572.75 21.428571     D
    >> 3  -223.75 35.714286    GL
    >> 4   123.25 50.000000    DG
    >> 5   359.75 64.285714     G
    >> 6   374.75 78.571429   DGL
    >> 7   821.75 92.857143    DL
    >> 
    >> Thanks in advance!
    >> 
    >> Seth Imhoff