R help - Oct 2011 - using predict.lm() within a function

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

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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>