[R] test if all predictors in a glm object are factors

[Prof Brian Ripley]

On Wed, 3 Sep 2008, Marc Schwartz wrote:

> on 09/03/2008 04:56 PM Michael Friendly wrote:
>> I'm trying to develop some graphic methods for glm objects, but they
>> only apply for models
>> where all predictors are discrete factors.  How can I test for this in a

Is an ordered factor a 'discrete factor'?  I suspect it is, so this needs 
to be

is.discrete.glm <- function(model)
   all(attr(terms(model), "dataClasses")[-1] %in% c("factor", "ordered"))

(removing redundant braces).



>> function, given the
>> glm model object?
>>
>> That is, I want something that will serve as an equivalent of
>> is.discrete.glm() in the following
>> context:
>>
>> myplot.glm <-
>> function(model, ...) {
>>    if (!inherits(model,"glm")) stop("requires a glm object")
>>    if (!is.discrete.glm(model)) stop("only factors are allowed")
>> ...
>> }
>>
>> A small example, for count data, a poisson glm:
>>
>> GSS <- data.frame(
>>  expand.grid(sex=c("female", "male"), party=c("dem", "indep", "rep")),
>>  count=c(279,165,73,47,225,191))
>>
>> mod.glm <- glm(count ~ sex + party, family = poisson, data = GSS)
>>
>> So, the model terms are sex and party, both factors.  Peeking inside
>> mod.glm, I
>> can find
>>
>>> mod.glm$xlevels
>> $sex
>> [1] "female" "male"
>> $party
>> [1] "dem"   "indep" "rep"
>> and, in str(mod.glm$model) I see
>>
>>> str(mod.glm$model)
>> 'data.frame':   6 obs. of  3 variables:
>> $ count: num  279 165 73 47 225 191
>> $ sex  : Factor w/ 2 levels "female","male": 1 2 1 2 1 2
>> $ party: Factor w/ 3 levels "dem","indep",..: 1 1 2 2 3 3
>> - attr(*, "terms")=Classes 'terms', 'formula' length 3 count ~ sex + party
>>  ....
>>
>> so this is a keeper.  Can someone help me improve on the following
>> is.discrete.glm() function.
>> It works for mod.glm, but isn't very general ;-)
>>
>> is.discrete.glm <- function(model) {
>>    TRUE
>> }
>>
>
> Michael,
>
> How about something like this:
>
> is.discrete.glm <- function(model) {
>  all(attr(terms(model), "dataClasses")[-1] == "factor")
> }
>
>
> Essentially, take the output of terms(model), check the 'dataClasses'
> attribute, except for the first element, which is the DV.
>
>> is.discrete.glm(mod.glm)
> [1] TRUE
>
>
> HTH,
>
> Marc Schwartz
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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