First, 'subset' is an argument to glm(), but for some reason you did not
use it. Your subject line is quite misleading, and had it been the more
accurate
Adding a 'data' argument to glm messes up factors?
you might have realised the problem.
Second, your models are fitted to different datasets: the first to objects
in your workspace, and the second to columns of data.all. Since you have
not (as we asked) given a reproducible example we cannot know what those
differences are, but differences in the datasets will be the key.
Third, the best way to fit linear models is lm(), not
glm(family=gaussian).
On Fri, 7 Dec 2007, Muri Soares wrote:
> I have a problem with running a glm using a subset of my data. Whenever
> I choose a subset, in the summary the factors arent shown (as if the
> variable was a continuous variable). If I dont use subsets then all the
> factors are shown. I have copied the output from summary for both cases.
>
> Thanks for the help,
> Muri
>
>> model<-glm(log(cpue)~year,family=gaussian)
> Call:
> glm(formula = log(cpue) ~ year, family = gaussian)
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.0962 -0.5851 -0.1241 0.4805 3.9236
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 0.8899 0.1844 4.825 1.42e-06 ***
> year1990 -0.6107 0.1925 -3.173 0.00152 **
> year1991 -1.7466 0.1902 -9.184 < 2e-16 ***
> year1992 -1.4061 0.1864 -7.544 5.07e-14 ***
> year1993 -1.4069 0.1860 -7.565 4.31e-14 ***
> ...
>
>>
model<-glm(log(cpue)~year,family=gaussian,subset(data.all,species=="n")
> Call:
> glm(formula = log(cpue) ~ year, family = gaussian, data = subset(data.all,
> species == "n"))
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.64577 -0.61671 -0.08972 0.55792 2.73737
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 32.446570 10.076895 3.220 0.00135 **
> year -0.016345 0.005037 -3.245 0.00123 **
> ---
> [[alternative HTML version deleted]]
>
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PLEASE do!
--
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)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595