similar to: Iterative sampling with restrictions

Hello All, I have posted to this list before regarding the same issue so I apologize for the multiple e-mails. I am still struggling with this issue so I thought I'd give it another try. This time I have included reproducible code and a subset of the data I am analyzing. I am running an ANOVA with three factors: GROUP (5 levels), FEATURE (2 levels), and PATIENT (2 levels), where

Dear list, I would like to do some calculation using different grouping variables. My 'df' looks like this: # Some data set.seed(345) id <- seq(200,400, by=10) ids <- sample(substr(id,1,1)) group1 <- rep(1:3, each=7) group2 <- rep(1:2, c(10,11)) group3 <- rep(1:4, c(5,5,5,6)) df <- data.frame(id, ids, group1, group2, group3) df <- rbind(df, df, df) df$time <-

Hi, I just get a question (sorry if it is a dumb one) and I "phase" my question in the following R codes: group1<-rnorm(n=50, mean=0, sd=1) group2<-rnorm(n=20, mean=1, sd=1.5) group3<-c(group1,group2) Now, if I am given a dataset from group3, what method (discriminant analysis, clustering, maybe) is the best to cluster them by using R. The known info includes: 2 clusters,

Hello sir: group1:1,2,3,4 group2:1,3,4,5 group3:2,4,8,9 .. ... group1000:9,3,8,2 I wanna get the "intersection set" and "union set". I've tried command "setdiff"and "union",but only two groups is permited.How can I deal with multi groups to find the "intersection set" and "union set"? Thanks a lot! My best

Hi, For further calculations I need to extract indivdual Variances of different random effects from a fitted model. I found out how to extract the correlations (VarCorr(m1)@reSumry$group1) but I was not able to find a way to extract the other components individually. To extract the Residuals I tried: (ranef(m1)@ stdErr) which unfortunately did not work. Thank you very much for your help!

Dear all, I'm performing a t-test on two normal distributions with identical mean & standard deviation, and repeating this tests a very large number of times to describe an representative p value distribution in a null case. As a part of this, the program bins these values in 10 evenly distributed bins between 0 and 1 and reports the number of observations in each bin. What I have noticed

Dear all, First, let's create some data to play around: set.seed(1) (df <- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10), Value=c(rexp(10, 1), rexp(10, 4), rexp(10, 10)))[sample(1:30,30),]) ## Now we need the empirical distribution function: edf <- function(x) ecdf(x)(x) # empirical distribution function evaluated at x ##

Dear list, I am confused on how to explain the interaction term in the context of "treatment contrast". for example, I have an data frame as below: sub group val 1 a group1 3.685625 2 a group1 3.407445 3 a group1 4.040920 4 a group1 2.890875 5 b group1 3.853280 6 b group1 4.113585 7 b group1 3.043250 8 b group1 3.800920 9 c group1 5.394305 10 c

Hello, unfortunately, I don't know a better subject. I would like to be very flexible in how to process my data. Assume the following dataset: par1 <- seq(0,1,length.out = 100) par2 <- seq(1,100) fac1 <- factor(rep(c("group1", "group2"), each = 50)) fac2 <- factor(rep(c("group3", "group4", "group5", "group6"), each =

I maintain a directory structure containing dirs and files that I regularly push to ~50 hosts, which are divided into 3 groups that have slightly different needs (minor mods in a couple of files). So ideally I would have 4 directories: /path/to/sync/common/ <- common files /path/to/sync/group1/ <- group1 specific only /path/to/sync/group2/ <- group2 specific only

Is there a way of positioning the color key in levelplot when the axes are on a categorical (rather than numerical) scale? I've put some sample code below. I need to add a secondary y axis to the right side of my plot but then the labels interfere with the color key (which is currently on the right side). Is there a way to shift the color key over a bit more to the right? I've tried

Dear friends, My R*C table is as follow: better good bad Goup1 16 71 37 Group2 0 4 61 Group3 1 6 57 Can I test if there are statistical significant between Group1 and Group2, Group2 and Group3, Group1 and Group2, taking into the multiple comparisons? The table can be set up using the following program: a<-matrix(data=c(16,71,37,0,4,61,1,6,57),nrow=3,byrow=TRUE) Thanks

Hello Instead of reading in group1.txt I want to read in groups1 for the first iteration of i, then groups2 for the second and so on. Obviously I can't use groups(i) but assume there is a way to do this. group<-read.table("C:/Data/April 2005/group1.txt",header=T) thanks in advance Meredith

Hello, i got a msdfs share running and now i want to hide folders from users who got no access to them anyway. For example: List of shares: test1 test2 User sees only: test1 Is something like that possible mit samba itself or does someone know a workaround to get it running like that ? Thanks for any ideas. A.Dura

If I have 3 groups,and for each group,I get the ratio(e.g. incidence rate). Now I wanna compare 3 ratio pairwise,and get the corresponding p values,i.e: group1 vs group2 ,p value=? group1 vs group3 ,p value=? group2 vs group3 ,p value=? Which statistical test should be used? Thanks a lot for your help. [[alternative HTML version deleted]]

Dear List, I am looking to perform exploratory analyses of two (relatively) large datasets of categorical data. The first one is a binary 80x100 matrix, in the form: matrix(sample(c(0,1),25,replace=TRUE), nrow = 5, ncol=5, dimnames = list(c( "group1", "group2","group3", "group4","group5"), c("V.1", "V.2", "V.3",

Hi all, I'd appreciate any pointers or advise regarding the following issue with files written by M$ Office on Samba 3.0.32 on snv_98 (OpenSolaris) on a ZFS filesystem: samba share: [sharename] read only = No browseable = yes writeable = yes directory mask = 0770 create mask = 0770 delete readonly = Yes acl check permissions =

Hello All, I'm deploying NUT in a data center and I'm curious to know how others have gone about staging the shutdown of various systems. The systems are broken down into groups of importance, group1 being the most important group4 being the least. In the event of an outage take down group4 after 5 minutes, group3 after 10 minutes, group2 after 15, and finally group4 after 20. I've

I'm creating a stacked bar chart using the likert command in the HH package. My data are in a data frame, with two numeric variables and a categorical variable, I can't get likert to use the column containing the categorical variable as a my y axis label. Here is a quick example: library(HH) #my data are:

Sorry i had a misprint in the appendix code in the last email Hi I needed some help with ANOVA I have a problem with My ANOVA analysis. I have a dataset with a known ANOVA p-value, however I can not seem to re-create it in R. I have created a list (zzzanova) which contains 1)Intensity Values 2)Group Number (6 Different Groups) 3)Sample Number (54 different samples) this is created by the