[R] using predict.lm() within a function

[Dennis Murphy]

Hi Michael:

Try this:

show.beta <- function(model, x = 'x',
                      x1, x2, label, col="black", ...) {
   abline(model, col=col, lwd=2)
   xs <- data.frame(c(x1, x2, x2))
   names(xs) <- attr(model$coefficients, 'names')[2]
   ys <- predict(model, xs)
   lines(cbind(xs,ys[c(1,1,2)]), col=col)
   text(x2, mean(ys[1:2]), label, col=col, ...)
}

Both of your examples worked for me. The trick is to match the
variable name in the model with the variable name in the prediction
data frame. There are several ways to access that, but I chose the
first opportunity I saw:

> str(mod)
List of 12
 $ coefficients : Named num [1:2] 0.501 0.351
  ..- attr(*, "names")= chr [1:2] "(Intercept)" "xx"

The line where I assign the names to xs is where the attr() function
comes into play. The first argument is the choice of list component
from the model object, while the second is the name of the attribute
to extract. This one returns a vector whose second component is what
we want.

HTH,
Dennis

On Mon, Oct 24, 2011 at 2:30 PM, Michael Friendly <friendly at yorku.ca> wrote:
> I've written a simple function to draw a regression line in a plot and
> annotate the line showing the slope
> with a label.  It works, as I'm using it, when the horizontal variable is
> 'x', but gives incorrect results otherwise.
> What's wrong?
>
> # simple function to show the slope of a line
> show.beta <- function(model, x="x", x1, x2, label, col="black", ...) {
>    abline(model, col=col, lwd=2)
> #    x <- deparse(substitute(x))      # doesn't help
>    xs <- data.frame(x=c(x1, x2, x2))
>    ys <- predict(model, xs)
>    lines(cbind(xs,ys[c(1,1,2)]), col=col)
>    text(x2, mean(ys[1:2]), label, col=col, ...)
> }
>
> x=rnorm(10)
> DF <- data.frame(x, y=.25*x+rnorm(10))
>
> # OK
> with(DF, {
>    plot(y ~ x)
>    mod <- lm(y ~ x)
>    show.beta(mod, "x", -0.5, 0, "b", pos=4)
>    })
>
> # not OK
> xx=rnorm(10)
> DF2 <- data.frame(xx, y=.25*x+rnorm(10))
>
> with(DF2, {
>    plot(y ~ xx)
>    mod <- lm(y ~ xx)
>    show.beta(mod, "xx", -0.5, 0, "b", pos=4)
>    })
>
> From the latter, I get:
>
> Warning message:
> 'newdata' had 3 rows but variable(s) found have 10 rows
>>
>
>
>
> --
> Michael Friendly     Email: friendly AT yorku DOT ca
> Professor, Psychology Dept.
> York University      Voice: 416 736-5115 x66249 Fax: 416 736-5814
> 4700 Keele Street    Web:   http://www.datavis.ca
> Toronto, ONT  M3J 1P3 CANADA
>
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