similar to: contrast package tutorial

I have the following code. I'm wondering why summary() doesn't show F value and Pr? Rscript multi_factor.R > a=3 > b=4 > c=5 > d=6 > e=7 > > A=1:a > B=1:b > C=1:c > D=1:d > E=1:e > > X=matrix(nr=a*b*c*d*e,nc=5) > colnames(X)=LETTERS[1:5] > > for(i_a in 1:a-1) { + for(i_b in 1:b-1) { + for(i_c in 1:c-1) { + for(i_d in 1:d-1) { +

I read somewhere that t.test is equivalent to a hypothesis testing for one way ANOVA. But I'm wondering how they are equivalent. In the following code, the p-value by t.test() is not the same from the value in the last command. Could somebody let me know where I am wrong? > set.seed(0) > N1=10 > N2=10 > x=rnorm(N1) > y=rnorm(N2) > t.test(x,y) Welch Two Sample t-test data:

Hi, I don't understand what the meaning of the following lines returned by model.matrix(). Can somebody help me understand it? What can they be used for? attr(,"assign") [1] 0 1 2 2 attr(,"contrasts") attr(,"contrasts")$A [1] "contr.treatment" attr(,"contrasts")$B [1] "contr.treatment" Regards, Peng > a=2 > b=3 > n=4

I have the R code at the end. The last command gives me "1 observation deleted due to missingness". I don't understand what this error message. Could somebody help me understand it and how to fix the problem? > summary(afit) Df Sum Sq Mean Sq F value Pr(>F) A 2 0.328 0.16382 0.1899 0.82727 B 3 2.882 0.96057 1.1136 0.34644 C

Hi, I run the following commands. 'A' has 3 levels and 'B' has 4 levels. Should there be totally 3+4 = 7 coefficients (A1, A2, A3, B1, B2, B3, B4)? > a=3 > b=4 > n=1000 > A = rep(sapply(1:a,function(x){rep(x,n)}),b) > B = as.vector(sapply(sapply(1:b, function(x){rep(x,n)}), function(x){rep(x,a)})) > Y = A + B + rnorm(a*b*n) > > fr =

Hi, I don't quite understand what are the return values of aov. I know that it has 'coefficients'. But I need to know what all the other return values are. Can somebody let me know how to figure them? Value: An object of class 'c("aov", "lm")' or for multiple responses of class 'c("maov", "aov", "mlm",

Hi, I want to do ANOVA for nested designs like following. I don't understand why the matrix (t(X) %*% X) is singular. Can somebody help me understand it? Regards, Peng > a=2 > b=3 > n=4 > A = as.vector(sapply(1:a,function(x){rep(x,b*n)})) > B = as.vector(sapply(1:(a*b), function(x){rep(x,n)})) > cbind(A,B) A B [1,] 1 1 [2,] 1 1 [3,] 1 1 [4,] 1 1 [5,] 1 2 [6,] 1 2 [7,]

Hi, I'm learning the tutorial. http://llvm.org/docs/tutorial/ I'm wondering if there is already a git repository of the examples in the tutorial so that I don't have to copy the code from the webpage. Thanks! -- Regards, Peng

Hi, I am looking for a complete description of the syntax of the formula that shall be specified in, for example, aov. But I can't find a complete description. Can somebody point to me if there is such a resource? Regards, Peng

How do we specify a contrast interaction matrix for an ANOVA model? We have a two-factor, repeated measures design, with Cue Direction (2) x Brain Hemisphere(2) Each of these has 2 levels, 'left' and 'right', so it's a simple 2x2 design matrix. We have 8 subjects in each cell (a balanced design) and we want to specify the interaction contrast so that: CueLeft>CueRght

Hello Peng Yu, I found the same error on my Macbook Air. This was my first trying on MacOS X. Troubleshooting this might take sometime. Only thing I can say now that klang is tested successfully on Ubuntu with - LLVM 3.2 official release on LLVM download page - LLVM svn latest update Clang compile produces an error message on MacOS X with the LLVM svn latest update I am trying to find the

Hello, In a book (David W. Stockburger, "Multivariate Statistics: Concepts, Models, and Applications", chapter 12 "Contrasts, Special and Otherwise", available online at http://www.psychstat.smsu.edu/multibook) I've found some examples of doing analysis of variance on a contrast basis. I attach my solution (in R, the book uses SPSS) to this problem. Am I computing the

Hello Peng Yu and List, I have put toy.cpp into github but it has a form of LLVM project makefile infrastructure. So you can build it together with LLVM Project source tree. git://github.com/Journeyer/klang.git There exist many branches and each branch is for each chapter of Kaleidoscope. Regards Journeyer 2012/12/30 Peng Yu <pengyu.ut at gmail.com>: > Hi, > > I'm learning

The man page for se.contrast, when describing the contrast.obj parameter, states that "Multiple contrasts should be specified by a matrix as returned by contrasts." When doing an unbalanced single factor ANOVA, using a contrast.obj as returned by contrasts results in the following error from qr.qty when se.contrast is called: Error in qr.qty(object$qr, contrast) : qr and y must have

Hello, I've got what I'd expect to be a pretty simple issue: I fit an aov object using multiple error strata, and would like some significance tests for the contrasts I specified. In this contrived example, I model some test score as the interaction of a subject's gender and two emotion variables (angry, happy, neutral), measured at entry to the experiment (entry) and later

Hello all, (Apologies in advance if my terminology is incorrect, I'm relatively new to R and statistics). I have data from a factorial design with two treatments (CRF-23), and I'm trying to compute treatment-contrast interactions through analysis of variance. I can't figure out how to do contrasts properly, despite reading the help for "C" and "contrasts"

On Sat, Dec 29, 2012 at 7:30 PM, Journeyer J. Joh <oosaprogrammer at gmail.com> wrote: > Hello Peng Yu and List, > > I have put toy.cpp into github but it has a form of LLVM project > makefile infrastructure. So you can build it together with LLVM > Project source tree. > > git://github.com/Journeyer/klang.git > > There exist many branches and each branch is for

Hi, For a n-level factor, I'd like to specify the first contrast and have the remaining n-2 constructed automatically so that the set is orthogonal. I then test the contrasts with summary.lm(anova-object). In S-Plus, the following works: >y.anova <- aov( y ~ C(CO2,c(1,0,-1)) ) >summary.lm(y.anova) In R, it fails with the following error: >levels(CO2) [1]

Klang is tested with LLVM 3.1 Header file location is often changed. I guess that's why.. What version of LLVM do you use? 2012/12/30 Peng Yu <pengyu.ut at gmail.com>: > On Sat, Dec 29, 2012 at 7:30 PM, Journeyer J. Joh > <oosaprogrammer at gmail.com> wrote: >> Hello Peng Yu and List, >> >> I have put toy.cpp into github but it has a form of LLVM project

I am having trouble getting standard errors for contrasts using se.contrast() in what appears to be a simple case to me. The following test example illustrates my problem: Lab <- factor(rep(c("1","2","3"),each=12)) Material <- factor(rep(c("A","B","C","D"),each=3,times=3)) Measurement <-