[R] Measure of linearity between two variables?
Spencer Graves
spencer.graves at pdf.com
Thu Apr 17 20:44:08 CEST 2003
Could you be more specific about what you want?
For example, do you want a statistical test with a significance
probability or a measure like R^2? Also, are your numbers bounded,
e.g., between 0 and 1? What kind of error structure is inherent in the
application? Should we think about transforming the response variable
or using "glm" or nonlinear regression?
If I were concerned about saturation at either end, perhaps the
simpliest thing might be to add a cubic to what you considered:
x ~ y + I(y^2) + I(y^3)
From this we could get significance probabilities for the squared and
cubic terms combined. Also, by converting the sum of squares column to
percent, we get something like R^2.
Hope this helps.
Spencer Graves
Paul, David A wrote:
> Maybe I'm missing something, but why not use the Pearson Product
> Moment Correlation Coefficient (r) ? It directly measures the strength
> of the linear relationship between two variables. A simple approach
> would be the following:
>
> (1) fix a percentage p of the data you are interested in
> (2) fix one of your two variables (x,y) as a reference - call
> it x
> (3) subset your data.frame down to those pairs (x*,y*)
> corresponding to the middle p percent of x
> (4) calculate r for the pairs (x*,y*)
>
> By doing (1) through (4) many time for increasing values of p
> I think you'll get what you want.
>
> Best,
> david paul
>
>
> -----Original Message-----
> From: Luke Whitaker [mailto:luke at inpharmatica.co.uk]
> Sent: Thursday, April 17, 2003 12:03 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Measure of linearity between two variables?
>
>
>
> Hello,
>
> I am looking for a measure of linearity in the relationship between two
> variables.
>
> Specifically, I have two variables for which the relationship is reasonably
> linear over a certain range of values, and then diverges from linearity at
> either end of the range, as one or other variable "saturates" at a maximum
> or minimum value. I want to identify the region of linearity, where neither
> variable has saturated.
>
> This is a problem that will be repeated many times so I want a programmatic
> solution. I am intending to implement some kind of search over the central
> range of values, expanding out and testing for linearity over each
> incrementally increased range. However, I need a measure if linearity.
>
> So far, I have thought of doing a regression on x ~ y + y^2, and using the
> absolute value of the ratio of coefficients of the squared and linear terms.
> Does anyone have any better ideas, either for a linearity measure or a
> different approach to finding the region of linearity between the two
> variables ?
>
> Thanks,
>
> Luke Whitaker
>
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