[R] reference on contr.helmert and typo on its help page.

[Peng Yu]

Dear John,

I did read Section 9.1.2 and various other textbooks before posting my
questions. But each reference uses slightly different notations and
terminology. I get confused and would like a description that
summaries everything so that I don't have to refer to many different
resources. May I ask a few questions on the section in your textbook?

Which variable in Section 9.1.2 is "a matrix of contrasts" mentioned
in the help page of 'contr.helmert'? Which matrix of contrast in R
corresponds to dummy regression? With different R formula, e.g. y ~ x
vs. y ~ x -1, $X_F$ (mentioned on page 189) is different and hence
$\beta_F$ (mentioned in eq. 9.3) is be different. So my understanding
is that the matrix of contrast should depend on the formula. But it is
not according to the help page of "contr.helmert".

Regards,
Peng

On Sun, Nov 8, 2009 at 6:17 PM, John Fox <jfox at mcmaster.ca> wrote:
> Dear Peng Yu,
>
> Perhaps you're referring to my text, Applied Linear Regression Analysis and
> Generalized Linear Models, since I seem to recall that you sent me a number
> of questions about it. See Section 9.1.2 on linear contrasts for the answer
> to your question.
>
> I hope this helps,
>  John
>
> --------------------------------
> John Fox
> Senator William McMaster
>  Professor of Social Statistics
> Department of Sociology
> McMaster University
> Hamilton, Ontario, Canada
> web: socserv.mcmaster.ca/jfox
>
>
>> -----Original Message-----
>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
> On
>> Behalf Of Peng Yu
>> Sent: November-08-09 4:52 PM
>> To: r-help at stat.math.ethz.ch
>> Subject: Re: [R] reference on contr.helmert and typo on its help page.
>>
>> On Sun, Nov 8, 2009 at 11:28 AM, Peter Dalgaard
>> <p.dalgaard at biostat.ku.dk> wrote:
>> > Gabor Grothendieck wrote:
>> >>
>> >> On Sun, Nov 8, 2009 at 11:59 AM, Peng Yu <pengyu.ut at gmail.com> wrote:
>> >>>
>> >>> On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch <murdoch at stats.uwo.ca>
>> >>> wrote:
>> >>>>
>> >>>> On 08/11/2009 11:03 AM, Peng Yu wrote:
>> >>>>>
>> >>>>> I'm wondering which textbook discussed the various contrast matrices
>> >>>>> mentioned in the help page of 'contr.helmert'. Could somebody let me
>> >>>>> know?
>> >>>>
>> >>>> Doesn't the reference on that page discuss them?
>> >>>
>> >>> It does explain what the functions are. But I need a more basic and
>> >>> complete reference. For example, I want to understand what 'Helmert
>> >>> parametrization' (on page 33 of 'Statistical Models in S') is.
>> >>>
>> >>
>> >> Just google for: Helmert contrasts
>> >
>> > Or,
>> >
>> >> contr.helmert(5)
>> >  [,1] [,2] [,3] [,4]
>> > 1   -1   -1   -1   -1
>> > 2    1   -1   -1   -1
>> > 3    0    2   -1   -1
>> > 4    0    0    3   -1
>> > 5    0    0    0    4
>> >
>> >> MASS::fractions(MASS::ginv(contr.helmert(5)))
>> >     [,1]  [,2]  [,3]  [,4]  [,5]
>> > [1,]  -1/2   1/2     0     0     0
>> > [2,]  -1/6  -1/6   1/3     0     0
>> > [3,] -1/12 -1/12 -1/12   1/4     0
>> > [4,] -1/20 -1/20 -1/20 -1/20   1/5
>> >
>> > and apply brains.
>> >
>> > I.e., except for a slightly odd multiplier, the parameters represent the
>> >  difference between each level and the average of the preceding levels.
>>
>> I realized that my questions are what a contrast matrix is and how it
>> is related to hypothesis testing. For a give hypothesis, how to get
>> the corresponding contrast matrix in a systematical way? There are
>> some online materials, but they are all diffused. I have also read the
>> book Applied Linear Regression Models, which doesn't give a complete
>> descriptions on all the aspects of contrast and contrast matrix. But I
>> would want a textbook that gives a complete description, so that I
>> don't have to look around for other materials.
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>
>