similar to: nested hierarchical design

I have two questions I would appreciate assistance with: (1) I believe "by" is the command used to split a file. In the following example, "mydat" is the dataframe , "group" the variable I want to split the analysis by & "WK1FREQ,WK2FREQ" the variables attach(mydat) by (GROUP) cor.test (WK1FREQ,WK2FREQ) I have also tried: (by (GROUP) cor.test

Hello everybody, This is my firth question in this mailing list. The question is about the how to deal with a model with both random and fixed factors. I know to do the analysis using SPSS. The command line wit be as follows: UNIANOVA alpha.ug.mg BY Line Year Rep /RANDOM=Year Rep /METHOD=SSTYPE(4) /INTERCEPT=EXCLUDE /PRINT=HOMOGENEITY /CRITERIA=ALPHA(0.05) /DESIGN= Year Rep*Year Line

Hi R-people I have a question concerning subsetting. I have a dataframe which contains among other variables the variable "subject". For each subject number there are several rows, e.g.: subject treatment concentration day 19 a 15,4 1 19 a 18,3 2 19 a 2,3 3 etc. Im trying to subset the dataframe to get for

I want to use the plot(model) function to generate Tukey-anscomb and Q-Q plots of a lm(). I manage to change all labels but the main one which apparently is neither main or sub. So far I have tried as par setting: cex (changes symbol size within the plot), cex.main (no effect), cex.sub (no effect) cex.lab (changes label size), cex.axis (changes axis label size). What I would like to change is the

Factor out all kernel specific path's (those containing usr/) into two variables: KLIBSRC + KLIBINC. Set the variables in a kernel spcific Kbuild file. Sam commit e6f989c1597a837f4aecbd11083697184c089611 tree 93f88d7564bb9e4d4bc95fd455b842d0bd0fdc54 parent 8151f4a98f82fba4fe3b949f49da4ab8bba71501 author Sam Ravnborg <sam@mars.(none)> Thu, 28 Jul 2005 23:36:07 +0200 committer Sam

GEN usr/klibc/syscalls/SYSCALLS.i GEN usr/klibc/syscalls/syscalls.nrs GEN usr/klibc/syscalls/typesize.c KLIBCCC usr/klibc/syscalls/typesize.o OBJCOPY usr/klibc/syscalls/typesize.bin GEN usr/klibc/syscalls/syscalls.mk GEN usr/klibc/syscalls/SYSCALLS.i GEN usr/klibc/syscalls/syscalls.nrs GEN usr/klibc/syscalls/typesize.c KLIBCCC

I don't think, this has been answered: > I'm trying to run a 3-way within-subject anova in lme with 3 > fixed factors (Trust, Sex, and Freq), but get stuck with handling > the random effects. As I want to include all the possible random > effects in the model, it would be something more or less > equivalent to using aov > > > fit.aov <- aov(Beta ~ >

Hi, Was wondering if anyone had any tips or experience in getting a Nortel CS1K and Asterisk 1.4.19 to talk to each other via NRS? So far I've gotten asterisk to place calls to the CS1k via the NRS, however calls originated by the CS1K get rejected by the NRS with a 404 Not Found message. If I take the NRS out of the equation by replacing the IP address of the NRS in the CS1K with that

I found a bug in one of the fourteen speed patches I posted, namely in patch-vec-subset. I've fixed this (I now see one does need to duplicate index vectors sometimes, though one can avoid it most of the time). I also split this patch in two, since it really has two different and independent parts. The patch-vec-subset patch now has only some straightforward (locally-checkable) speedups for

Hello everybody 1. If there is/ever will be a function to perform "duncan multiple range test" please inform me at once. 2. Is there a way to create a grouping as duncan does from TukeyHSD output? My experimental design contained 62 genotypes, so the pairwise comparison is not that usefull and clear to look at. How would I do that? Is there an other test that does give grouping as

What do I need to do to fix this? [jonsmirl@smirl klibc-0.184]$ make make[1]: Entering directory `/home/dri/klibc-0.184/klibc' gcc -Wp,-MT,syscalls.nrs,-MD,./.syscalls.nrs.d -mregparm=3 -DREGPARM=3 -march=i386 -Os -g -falign-functions=0 -falign-jumps=0 -falign-loops=0 -nostdinc -iwithprefix include -D__KLIBC__ -DBITSIZE=32 -I../include/arch/i386 -I../include/bits32 -I../include

Hi there I'm trying to find the mle fo a multinomial model ->*L(N,h,S?x)*. There is only *N* I want to estimate, which is used in the number of successes for the last cell probability. These successes are given by: p^(N-x1-x2-...xi) All the other parameters (i.e. h and S) I know from somewhere else. Here is what I've tried to do so far for a imaginary data set:

Hello, It seems that, unlike Splus, the anova.lm function of R does not take the argument ssType=3 into account. How can one get an anova table with the adjusted sum of squares in R? Thanks in advance, Patrick Giraudoux University of Franche-Comté Department of Environmental Biology EA3184 af. INRA F-25030 Besançon Cedex tel.: +33 381 665 745 fax.: +33 381 665 797 http://lbe.univ-fcomte.fr

This message contains a description of what looks like a bug, examples of the suspect behavior, a proposed change to the C code to change this behavior, example of behavior with the fix, and suggestions for 3 places to update the documentation to reflect the proposed behavior. It is submitted for consideration for inclusion in R. Comments are requested. Currently, the code for subscripting

I've put this in (with some different wording). Although S blithely accepts mis-dimensioned index matrices I agree this is wrong and have made it an error. On Fri, 29 Apr 2005 tplate@acm.org wrote: > This message contains a description of what looks like a bug, examples > of the suspect behavior, a proposed change to the C code to change this > behavior, example of behavior with

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I am trying to run a GLMM on some binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help

Dear all, As far as I understand, the number of arguments in methods:::cbind is limited by the "self recursive" construction of the function which generates nested loops. A workaround could be to use the internal cbind function on blocks of non S4 objects. The limitation would then be reduced to the number of consecutive S4 objects. ##### R code ##### dfr <- data.frame(matrix(0,

list, i am using lmer to fit multilevel models and trying to use anova to compare the models. however, whenever i run the anova, the AIC, BIC and loglik are different from the original model output- as below. can someone help me out with why this is happening? (i'm hoping the output assocaited with the anova is right!). thank you, darren > unconditional<-lmer(log50 ~ 1 + (1 |

I'm an SPSS user trying to make the transition to R. Can someone help me translate the following SPSS code into R?: GLM Total_tp1 Total_tp2 WITH Age Sex   /WSFACTOR=Time 2 Repeated   /METHOD=SSTYPE(3)   /CRITERIA=ALPHA(.05)   /WSDESIGN= Time   /DESIGN= Age Sex Age*Sex. Also. can anyone recommend any resources to help SPSS users learn to things in R? Thanks, -kristi [[alternative HTML