Re: [R] reference on contr.helmert and typo on its help page.
On Mon, 2009-11-09 at 19:31 -0600, Peng Yu wrote: > On Sun, Nov 8, 2009 at 7:32 PM, John Fox wrote: > > Dear Peng, > > > > I'm tempted to try to get an entry in the fortunes package but will instead > > try to answer your questions directly: > > I can not install 'fortunes'. What are the fortunes packages about? > > install.packages("fortunes", repos="http://R-Forge.R-project.org";) > Warning: unable to access index for repository > http://R-Forge.R-project.org/bin/macosx/leopard/contrib/2.9 > Warning message: > In getDependencies(pkgs, dependencies, available, lib) : > package ‘fortunes’ is not available It is on CRAN. just do: install.packages("fortunes") Choose a repository near to you and it should install. There appears to be a problem with R-forge and Mac OsX binaries. The code you show above works for me on linux and R2.9.x G > > >> 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". > > > > If the model is simply y ~ A, for the factor A, then cbind(1, contrasts(A)) > > is what I call X_B, the row-basis of the model matrix. As I explain in the > > section that you read, the level means are mu = X_B beta, and thus beta = > > X_B^-1 mu = 0 are the hypotheses tested by the contrasts. Moreover, if, as > > in Helmert contrasts, the columns of X_B are orthogonal, then so are the > > rows of X_B^-1, and the latter are simply rescalings of the former. That > > allows one conveniently to code the hypotheses directly in X_B; all this is > > also explained in that section of my book, and is essentially what Peter D. > > told you. In R, contr.treatment and contr.SAS provide dummy-variable (0/1) > > coding of regressors, differing only in the selection of the reference > > level. > > What is the mathematical definition of polynomial contrasts? Why > polynomial contrasts are the default contrasts for ordered factors? > > __ > R-help@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. -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% __ R-help@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.
Re: [R] reference on contr.helmert and typo on its help page.
On Sun, Nov 8, 2009 at 7:32 PM, John Fox wrote: > Dear Peng, > > I'm tempted to try to get an entry in the fortunes package but will instead > try to answer your questions directly: I can not install 'fortunes'. What are the fortunes packages about? > install.packages("fortunes", repos="http://R-Forge.R-project.org";) Warning: unable to access index for repository http://R-Forge.R-project.org/bin/macosx/leopard/contrib/2.9 Warning message: In getDependencies(pkgs, dependencies, available, lib) : package ‘fortunes’ is not available >> 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". > > If the model is simply y ~ A, for the factor A, then cbind(1, contrasts(A)) > is what I call X_B, the row-basis of the model matrix. As I explain in the > section that you read, the level means are mu = X_B beta, and thus beta = > X_B^-1 mu = 0 are the hypotheses tested by the contrasts. Moreover, if, as > in Helmert contrasts, the columns of X_B are orthogonal, then so are the > rows of X_B^-1, and the latter are simply rescalings of the former. That > allows one conveniently to code the hypotheses directly in X_B; all this is > also explained in that section of my book, and is essentially what Peter D. > told you. In R, contr.treatment and contr.SAS provide dummy-variable (0/1) > coding of regressors, differing only in the selection of the reference > level. What is the mathematical definition of polynomial contrasts? Why polynomial contrasts are the default contrasts for ordered factors? __ R-help@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.
Re: [R] reference on contr.helmert and typo on its help page.
Dear Peng, I'm tempted to try to get an entry in the fortunes package but will instead try to answer your questions directly: > -Original Message- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of Peng Yu > Sent: November-08-09 7:41 PM > To: r-h...@stat.math.ethz.ch > Subject: Re: [R] reference on contr.helmert and typo on its help page. > > 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". If the model is simply y ~ A, for the factor A, then cbind(1, contrasts(A)) is what I call X_B, the row-basis of the model matrix. As I explain in the section that you read, the level means are mu = X_B beta, and thus beta = X_B^-1 mu = 0 are the hypotheses tested by the contrasts. Moreover, if, as in Helmert contrasts, the columns of X_B are orthogonal, then so are the rows of X_B^-1, and the latter are simply rescalings of the former. That allows one conveniently to code the hypotheses directly in X_B; all this is also explained in that section of my book, and is essentially what Peter D. told you. In R, contr.treatment and contr.SAS provide dummy-variable (0/1) coding of regressors, differing only in the selection of the reference level. John > > Regards, > Peng > > On Sun, Nov 8, 2009 at 6:17 PM, John Fox 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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > > On > >> Behalf Of Peng Yu > >> Sent: November-08-09 4:52 PM > >> To: r-h...@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 > >> wrote: > >> > Gabor Grothendieck wrote: > >> >> > >> >> On Sun, Nov 8, 2009 at 11:59 AM, Peng Yu wrote: > >> >>> > >> >>> On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch > >> >>> 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))) > >
Re: [R] reference on contr.helmert and typo on its help page.
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 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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > On >> Behalf Of Peng Yu >> Sent: November-08-09 4:52 PM >> To: r-h...@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 >> wrote: >> > Gabor Grothendieck wrote: >> >> >> >> On Sun, Nov 8, 2009 at 11:59 AM, Peng Yu wrote: >> >>> >> >>> On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch >> >>> 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@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. > > > __ R-help@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.
Re: [R] reference on contr.helmert and typo on its help page.
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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of Peng Yu > Sent: November-08-09 4:52 PM > To: r-h...@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 > wrote: > > Gabor Grothendieck wrote: > >> > >> On Sun, Nov 8, 2009 at 11:59 AM, Peng Yu wrote: > >>> > >>> On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch > >>> 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@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. __ R-help@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.
Re: [R] reference on contr.helmert and typo on its help page.
On Sun, Nov 8, 2009 at 11:28 AM, Peter Dalgaard wrote: > Gabor Grothendieck wrote: >> >> On Sun, Nov 8, 2009 at 11:59 AM, Peng Yu wrote: >>> >>> On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch >>> 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@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.
Re: [R] reference on contr.helmert and typo on its help page.
Gabor Grothendieck wrote: On Sun, Nov 8, 2009 at 11:59 AM, Peng Yu wrote: On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch 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 21 -1 -1 -1 302 -1 -1 4003 -1 50004 > 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. -- O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - (p.dalga...@biostat.ku.dk) FAX: (+45) 35327907 __ R-help@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.
Re: [R] reference on contr.helmert and typo on its help page.
On Sun, Nov 8, 2009 at 11:59 AM, Peng Yu wrote: > On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch 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 __ R-help@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.
Re: [R] reference on contr.helmert and typo on its help page.
On Sun, Nov 8, 2009 at 10:11 AM, Duncan Murdoch 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. >> BTW, in R version 2.9.1, there is a typo on the help page of >> 'contr.helmert' ('cont.helmert' should be 'contr.helmert'). > > Thanks, I've fixed the typo. > > Duncan Murdoch > __ R-help@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.
Re: [R] reference on contr.helmert and typo on its help page.
On Nov 8, 2009, at 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? My version of "Modern Applied Statistics in S" (aka MASS) deals with it in enough detail for a person with background to understand. At one point I asked Ripley whether later editions of MASS expanded the coverage of that topic but my memory is that he did not reply. Coming from a perspective that emphasized regression, I found it rather terse (2 pages), so there might be one of the more recently published texts that spends more time developing the concepts from basics. "Statistical Models in S" also covers the topic (5 pages) in an early chapter, again at a level that assumes prior training in ANOVA models. BTW, in R version 2.9.1, there is a typo on the help page of 'contr.helmert' ('cont.helmert' should be 'contr.helmert'). __ -- David Winsemius, MD Heritage Laboratories West Hartford, CT __ R-help@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.
[R] reference on contr.helmert and typo on its help page.
I'm wondering which textbook discussed the various contrast matrices mentioned in the help page of 'contr.helmert'. Could somebody let me know? BTW, in R version 2.9.1, there is a typo on the help page of 'contr.helmert' ('cont.helmert' should be 'contr.helmert'). __ R-help@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.