similar to: Iterative process for reading in text files

I know I'm not supposed to use them... but they're just so easy! I have trouble defining an appropriate function for plyr or apply! data<-rnorm(144) groups1<-c('a','b','c','d') groups2<-c('aa','bb','cc','dd') machines<-1:12

Hello 1/ 'priors' is a table looking like: "W123" "T678" "S789" 23 42 11 12 35 9 etc 2/ WBS <- labels(priors) gives me a result of class list and length 1 looking like: "W123" "T678" "S789" I want to read W123 into X[1] as W, T687 into X[2] as T and S789 into X[3] as S using

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

Hi all, I'm working on a seemingly trivial problem that I can't figure out how to implement in R. I'd be most grateful for any help here. I want to do the following: first, randomly assign each of n units to one of g groups of size n/g. Then, randomly re-assign each of the n units to a different group (i.e., same as the first step, but the unit can't be assigned to a group to

Can someone help with a fairly simple task? I have a data set where I would like to insert a 0 time event between individuals: what I have: VAR DATE TIME CONC COVAR 1 NOV2 0.25 10 group1 1 NOV2 0.5 20 group1 1 NOV2 1 5 group1 1 NOV2 2 1 group1 1 NOV2 3 0.1 group1 2 NOV2 0.25 10

Hi All, Is there a simple way to convert a string such as c("A", "B" ,"C", "D") to a string of c("Group1", "Group1", "Group2", "Group2"). Naturally I could use the factor function as below but I don't like seeing that warning message (and I don't want to turn off warning messages). Perhaps a function

Hello! I am aggregating using a formula in aggregate - of the type: aggregate(cbind(var1,var2,var3)~factor1+factor2,sum,data=mydata) However, I actually have an object (vector of my variables to be aggregated): myvars<-c("var1","var2","var3") I'd like my aggregate formula (its "cbind" part) to be able to use my "myvars" object. Is it

Full_Name: Martha Nason Version: 2.0.1 OS: Windows XP Submission from: (NULL) (137.187.154.154) I am running simulations using fisher's test on 2 x c tables and a very small p.value from fisher's test (<2.2e-16) is returned as a negative number. Code follows. > set.seed(0) > nreps.outer <-7 > pvalue.fisher <- rep(NA,nreps.outer) > > population1 <- c(

Hello! I have my data frame "mydata" (below) and data frame "reference" - that contains all the dates I would like to be present in the final data frame. I am trying to merge them so that the the result data frame contains all 8 dates in both subgroups (i.e., Group1 should have 8 rows and Group2 too). But when I merge it it's not coming out this way. Any hint would be

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

Hi all Assume I have a data set xx; Group: 1=group1 ?, 2=group2 IQ: ?1= High, 0 =low fit <- glm(IQ ~group, data = xx, family = binomial()) summary(fit) Results ?????? ????????????Estimate Std. Error z value Pr(>|z|) (Intercept) -2.55456??? 0.210 -12.273? < 5e-16 *** group????????? 0.36180 ?????0.076?? 3.952 ????5.24e-05 *** the odd ratio = exp(0.36180 )= 1.435912 My question

Hi, To pretty print aggregates by various dimensions I needed to add a empty row in output of aggregate. For example. d<-(aggregate(data[,cbind("x")], by=list(data$group1,data$group2), sum)) Group.1 Group.2 x 1 A N 3 2 A Y 2 3 B N 420164905 Is there a way to add an empty

Hi all, I would like to transform to long format a matrix which has only information about individuals and a value for each individual. I would like to have it in ling format with more information related to groups, so ell values and individuals are repeated for each group. Let me show the example: matrix in wide format: Individuals Value A 3 B 4 C 5 D 2 And long format would

Hello. Im hoping someone can help with a grouping question related to the "random=" statement within the nlme function. How do you specify that some grouping levels are inner to others? I tried several things, given below. Lets say I have a data frame with five variables, resp, cov1, ran1, ran2, group1, and group 2. The formula is resp~cov1 + ran1 + ran2, where the ran are random

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 all, I have a (simple?) question about groups. this is my scenario: Windows Active directory domain Samba file server ADS integrated 2 shares on this last server (share1, share2) 2 groups on the AD (group1 and group2) First share is only fully available to group1: this is easily done second share is fully available to group2 --- Then I have some users belonging to both group1 and

Hello, I'm Oliver and I need help for a experiment. I have a sharing with Samba version 3.2.5, my distribution Linux is Debian(Lenny) and the acl version is 2.2.47. Below my configurations files: #/etc/fstab /dev/sda3 /shared reiserfs defaults,acl 0 1 #smb.conf [data] comment = files path = /shared inherit acls = yes inherit permissions = yes map acl inherit = Yes #

Hi, Could someone please tell me how to perform a Mann-Whitney U test on a dataset with 2 groups where one group has more data values than another? I have split up my 2 groups into 2 columns in my .txt file i'm using with R. Here is the code i have so far... group1 <- c(LeafArea2) group2 <- c(LeafArea1) wilcox.test(group1, group2) This code works for datasets with the same number

Let me modify my question about user-defined covariance structures for LME models: Can somebody tell me how I can see the code for the definition of the correlation structures that come with the NLME package. Specifically I like to see the code for the functions coef, corMatrix, and intialize for any of the pre-defined correlation structures, and use this as a template to define a new correlation

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