[R] lm help: using lm when one point is known (not y intercept)
Martin Maechler
maechler at stat.math.ethz.ch
Mon Nov 29 10:36:22 CET 2004
>>>>> "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
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