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

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

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"

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 <-