Re: [Rd] using predict method with an offset

[Prof Brian Ripley]

The para quoted dates from before the stats package was split off in 
2003, and is historical (it was true at one point, but not in R 
2.0.0, the earliest running version I have).

There is however still some truth lurking there: the code is
        offset <- if (!is.null(off.num <- attr(tt, "offset")))
            eval(attr(tt, "variables")[[off.num+1]], newdata)
        else if (!is.null(object$offset))
            eval(object$call$offset, newdata)

so if there is an offset term in the formula, the offset argument is 
ignored (unlike when fitting).  Further, this is wrong if there is 
more than one offset term.  Both of those would be pretty unusual, but 
I'll commit fixes for them.

predict.glm calls predict.lm to do this, so the same issues apply to 
it.

I've always thought that an 'offset' argument to lm and glm was an 
unnecessary complication (I think it predates the offset() function in 
R, although it is in the White Book p.222, for glm only).

On Fri, 27 Feb 2009, Heather Turner wrote:

Hi Ken,

First of all, whether you specify the offset by the argument or in the
formula, your code requires that q25 is the same length as the variable
Contr. You can set this up by defining your new data as follows:

nd <- data.frame( Contr = cc , q25 = qlogis(0.25))

This sorts out the problem of the warnings/errors. Secondly your two
calls to predict give different results because you have not specified
the same type - the first is predicting on the response scale and the
second is predicting on the link scale. If you use

predict(c1.glm, newdata = nd, type = "response")
predict(c1f.glm, newdata = nd, type = "response")

you get the same result. This does seem to go against the documentation
however, so it would seem that the paragraph you quoted should be taken
out of the help file for predict.lm.

Best wishes,

Heather

Kenneth Knoblauch wrote:
Hi,

I have run into another problem using offsets, this time with
the predict function, where there seems to be a contradiction
again between the behavior and the help page.

On the man page for predict.lm, it says

Offsets specified by offset in the fit by lm will not be included in
predictions, whereas those specified by an offset term in the formula
will be.

While it indicates nothings about offsets under ?predict.glm, predict.glm
calls predict.lm. when there is a newdata argument.

In the example below, the behavior is the opposite of the help
page, if I am understanding it correctly, and a warning is thrown
when it does seem to work as desired.

c1 <- structure(list(Contr = c(0.028, 0.043, 0.064, 0.097, 0.146, 0.219
), Correct = c(34L, 57L, 94L, 152L, 160L, 160L), Incorrect = c(126L,
103L, 66L, 8L, 0L, 0L)), .Names = c("Contr", "Correct", "Incorrect"
), row.names = c("13", "15", "17", "19", "21", "23"), class = "data.frame")

q25 <- rep( qlogis( 0.25 ), nrow(c1) )

# offset defined in arguments
c1.glm <- glm( cbind(Correct, Incorrect) ~ Contr - 1, binomial,
    c1, offset = q25 )
# offset defined in formula
c1f.glm <- glm( cbind(Correct, Incorrect) ~ Contr + offset(q25) -1,
    binomial, c1 )
cc <- seq( 0, 1, len = 10 )
nd <- data.frame( Contr = cc )

When predict used with model for which offset was defined in
the arguments, offset is taken into account and a warning
is emitted.

predict(c1.glm, newdata = nd, type = "response")

        1         2         3         4         5         6         7
0.2500000 0.8859251 0.9945037 0.9997628 0.9999898 0.9999996 1.0000000
        8         9        10
1.0000000 1.0000000 1.0000000
Warning message:
In predictor + offset :
  longer object length is not a multiple of shorter object length

When predict used with model for which offset was defined in
the formula, an error occurs

predict( c1f.glm, newdata = nd )

Error in model.frame.default(Terms, newdata, na.action = na.action, xlev
= object$xlevels) :
  variable lengths differ (found for 'offset(q25)')

even if a column for offset is included in newdata,

ndf <- cbind( nd, "offset(q25)" = rep( qlogis(0.25), length(cc) ) )
predict( c1f.glm, newdata = ndf )

Error in model.frame.default(Terms, newdata, na.action = na.action, xlev
= object$xlevels) :
  variable lengths differ (found for 'offset(q25)')

unless there is a special way to specify the offset to predict
that I haven't been able to figure out.

traceback indicates the problem, again, with model.frame.default

Thank you for any clarification.

best,

Ken



______________________________________________
R-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-devel


--
Brian D. Ripley,                  rip...@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

______________________________________________
R-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-devel