[R] Dealing with data

[TGS]

# I wasn't trying to do ANOVA. I was simply trying to figure out how regress count on sprays (this is after I saw another poster asking an unrelated question with the InsectSprays dataset).
# 
# Anyhow, David clarified this but also, thanks for your explanation as well.

rm(list = ls()); sprays <- as.numeric(InsectSprays$spray)

lm(formula = count ~ 0 + spray, data = InsectSprays)
lm(formula = count ~ 0 + sprays, data = InsectSprays)

# besides the point, in the ANOVA problem the degrees of freedom would be 5, not 1.

On Aug 13, 2010, at 12:27 PM, Greg Snow wrote:

So you want 1 degree of freedom for InsectSprays?  You believe that the difference between A and B is exactly the same as between B and C which is exactly the same as between D and E (etc.)?  that seems an odd assumption, but you can get that by using as.numeric (as I and others have already stated).

If on the other hand you want InsectSprays to be treated correctly with the correct number of degrees of freedom, but have the output on a single line testing the overall effect, then you want to use the aov function rather than lm (internally they do the same thing, but the default summary output for aov is 1 line per term).

Hope this helps,

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111


> -----Original Message-----
> From: TGS [mailto:cran.questions at gmail.com]
> Sent: Friday, August 13, 2010 11:51 AM
> To: Greg Snow
> Cc: r-help at r-project.org
> Subject: Re: [R] Dealing with data
> 
> # Greg, if R automatically does that then I don't know why it's
> treating each indicator
> # as a different regressor. In other words, I am interested in treating
> 'spray' as one
> # independent variable.
> #
> # Erik, which book do you suggest I read? Thanks.
> 
> data(InsectSprays)
> lm(InsectSprays$count ~ 0 + InsectSprays$spray)
> 
> On Aug 13, 2010, at 10:34 AM, Greg Snow wrote:
> 
> R/S does all of that automatically for you, you do not need to manually
> create the indicator variables.
> 
> If you do something like:
> 
>> fit <- lm( Sepal.Width ~ Species, data=iris, x=TRUE)
> 
> Then look at the matrix actually used:
> 
>> fit$x
> 
> Or the output:
> 
>> summary(fit)
> 
> You will see that Species was automatically converted into indicator
> variables and those were used in the regression.
> 
> If you really need the indicator variables yourself, look at the
> model.matrix function, e.g.:
> 
>> model.matrix( ~Species, data=iris )
> 
> Or
> 
>> model.matrix( ~Species - 1, data=iris )
> 
> If you really want 1 for A, 2 for B, etc. then look at as.numeric on a
> factor variable (e.g. as.numeric(iris$Species) ).
> 
> Hope this helps,
> 
> --
> Gregory (Greg) L. Snow Ph.D.
> Statistical Data Center
> Intermountain Healthcare
> greg.snow at imail.org
> 801.408.8111
> 
> 
>> -----Original Message-----
>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
>> project.org] On Behalf Of TGS
>> Sent: Friday, August 13, 2010 11:22 AM
>> To: David Winsemius
>> Cc: r-help at r-project.org
>> Subject: Re: [R] Dealing with data
>> 
>> To clarify, I'd like to create a column of indicators for the
>> respective letters so that I could maybe do regression on indicators,
>> etc.
>> 
>> For instance, "A" gets "1", "B" gets "2", and so on.
>> 
>> On Aug 13, 2010, at 10:19 AM, David Winsemius wrote:
>> 
>> 
>> On Aug 13, 2010, at 1:03 PM, TGS wrote:
>> 
>>> # how would I code in R to look at the letter of the alphabet
>>> # in the second column and create a indicator column for the
>>> # corresponding letter?
>>> 
>>> data(InsectSprays)
>>> InsectSprays$spray
>> 
>> It's already what most people mean when they say "indicator column",
>> i.e., a factor variable (and not a character vector) .... so,  what
> do
>> _you_ mean?
>>> 
>> 
>> 
>> --
>> 
>> David Winsemius, MD
>> West Hartford, CT
>> 
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