similar to: a question about subsetting

Hi all, I have been struggling with ANOVAs on R. I am new to R, so I created a simple data frame, and I do some analyses on R just to learn R and then check them on SPSS to make sure that I am doing fine. Here is the problem that I've run into: when we use the aov function, it uses SS Type I as default (on SPSS it is Type III). Then I used the Anova function under cars package using the

##I want to remove the rows where the row sums are zero and this is as far as I have gotten ffg <- (structure(list(CD = c(0, 0, 0, 0, 3.125, 0, 0, 0, 0, 1.6, 3.125, 0, 0, 6.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0,

Hi I am really new using R, so this is really a beginner stuff! I created a very small data set on excel and then converted it to .csv file. I am able to open the data on R using the command "read.table ("mydata1.csv", sep=",", header=T)" and it just works fine. But when I want to work on the data (e.g. calculate the mean of variable "X") R says

Hi all, I have a data set (df, n=10 for the sake of simplicity here) where I have two continuous variables (age and weight) and I also have a grouping variable (group, with two levels). I want to run correlations for each group separately (kind of similar to "split file" in SPSS). I've been experimenting with different functions, and I was able to do this correctly using ddply

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

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

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 r helpers! Below is the whole coding for my programme. Before proceed more further, let me explain for you. First of all, I need to compute trimmed mean. Till that step is ok. Then I need to compute ssdw which is sum of square deviation. If I do equal trimming at both tail of distribution that I chose, I will use the first ssd formulae which is "a". But if I am doing unequal

Hi, On my mail server I want to implement shared folders for each workgroup where there are many workgroups. One way would be to create a separate namespace for each workgroup. However, this does not scale well so I decided to use a single Shared mailbox and use ACLs: namespace public { separator = . prefix = Shared. location = maildir:/var/mail/shared:CONTROL=~/Maildir/shared } Each

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

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

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(

Hi, I have the following (M x N) matrix, where M = 10 and N =2 What I intend to do is to group index of (M) based on this condition of "x_mn" , namely For each M, If x_m1 > x_m2, assign index of M to Group1 otherwise assign index of M into Group 2 > x [,1] [,2] [1,] 4.482909e-01 0.55170907 [2,] 9.479594e-01 0.05204063 [3,] 8.923553e-01 0.10764474

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

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

Dear All, I apologize for this trivial question, I can not find the solution I try to use t.test function per line in the data.frame, But i dont'understand the error message my program is as follows group1<-gl(2,20) fun<-function(x){ m<-data.frame(group1,x) #anova(aov(x ~ group1, m)) t.est(x ~ group1,m) } ttest<- apply(data, 1, fun) Error in t.test.default(x = c(1, 1,

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

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 #

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

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