similar to: Inherit names ...

Hello, I have a simple question about using the aov function syntax (ie. * + or :) for the interaction of 2 factors. I have read the help files, and researched other sites, and have included my source files. My goal is to measure the signifigance of the interaction between population and condition (aka. population:condition). I can't seem to figure it out. 1. In the first example the

Hi all, I'm just a beginner with R but I have not been able to search for any relevant answer to my problem. I apologize if it has in fact been asked before. Recently I've realized that I need to combine hundreds of pairs of data frames. The filenames of the frames I need to combine have unique strings. This is my best guess as to the approach to take: filenames<-list.files()

HI All, I have a long data file generated from a minimal pair test that I gave to learners of Arabic before and after a phonetic training regime. For each of thirty some subjects there are 800 rows of data, from each of 400 items at pre and posttest. For each item the subject got correct, there is a 'C' in the column 'Correct'. The line: tapply(ALLDATA$Correct,

All, For example, I have a dataset named "ABC" loaded into R > ABC [,1] [,2] [,3] [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 and I also have a variable datasetname > datasetname [1] "ABC" and I want to add this "ABC" dataset to an existing list "alldata" > alldata <-NULL > alldata <- as.list(alldata) since I will

Dear all, I've come across a problem using strptime, can anyone explain what's going on? I'm using version 2.7.0 on Windows XP. Thank you Caroline First read in a data file using read.table alldata = read.table(file, header=F, skip=4, colClasses = c("character","numeric")) dim(alldata) [1] 223960 2 # inefficient, safe way of sorting out missing or dodgy

Hi R list, I would like to automate, or speed up the process from which I take several separate datasets, stored in .csv formate, import and merge them by a common variable. So far I have greatly sped up the loading process but cannot think of a way to automate the merger of all datasets into a common data.frame. My apologies if this has been covered, any R search suggestions are

Hello, I have a question regarding how to subset/select parts of a data frame (matrix) in order to plot data associated only with this subset. Specifically I have a large data frame in which one column contains ID values (dates), and other columns contain data I would like to plot (temperature, light, etc.). I would like to break up this large matrix so as to plot data associated

Dear R help list, I am very new to R and I apologize in advance if this has been answered before. I have done my best to google/R search what I need but no luck. Here is what I am attempting: I have hundreds of .csv files that I need to sort based on a single column of alphanumeric data. All of the files contain matrices that have identical dimensions and headers, however the data table

Hi everyone, my apologies in advance if I'm overlooking something simple in this question. I am trying to use R's survey package to make a direct method age-adjustment to some complex survey data. I have played with postStratify, calibrate, rake, and simply multiplying the base weights by the correct proportions - nothing seems to hit the published numbers on the nose. I am trying to

R 2.9.1 Windows XP I am fitting a random effects ANOVA with two factors Group which has two levels and Time which has three levels: fita<-lme(Post~Time+factor(Group)+factor(Group)*Time, random=~1|SS,data=blah$alldata) I want to get the omnibus significance tests for each factor and the interaction. I believe I can get the omnibus test for the interaction by running the model:

(R 1.9.1; Windows 2000;) I'm just comparing ease of use, speed, etc for methods of transferring data frames in the Excel, MySQL, R triangle. It turns out that going from Excel to R (when doing this carefully). Using the clipboard is actually quite fast and efficient (2 seconds for transferring 120 000 cells on a common desktop computer as compared to much longer for going the RODBC route,

Hello R-Help, ----------------------------------------------------------------------------------------------------------------------------------------- Issues (there are 2): 1) Possible bug when using lmtest::encomptest() with a linear model created using nlme::lmList() 2) Possible modification to lmtest::encomptest() to fix confusing fail when models provided are, in fact, nested. I have

Hi, Being in the process of translating some of my SAS programs to R, I encountered one difficulty. I have a solution, but it is not elegant (and not pleasant to implement). I have a large dataset with many variables needed to identify the origin of a sample, many to describe sample characteristics, others to describe site characteristics. I want only a (shorter) list of sites and their

Hi - I am trying to substitute for "the_other_y" in the code below. I want y2 and y3 to be there when i is 1, y1 and y3 to be there when i is 2 and y1 and y2 to be there when i is 3. I'm sure it's to do with what format the data should be in and I've tried alldata[,-i], but it fits all the columns of alldata except i rather than each column one at a time. I've tried

Hello all, I don't understand why this won't work. I have entered: WriteXLS(alldata,'test.xls') and I get this error message: Error in get(x, envir = envir) : variable names are limited to 256 bytes. My variable names are not very long, and are accepted by write.csv. alldata is a list containing 4 dataframes, with each dataframe having the the same variable names, which are:

I searched the mailing list archives and found one post relevant to my problem, but it was not specific enough to solve my problem. I am reading in a large file of data (I believe it is in ASCII format). I have tried reading the file in as a data frame and as a list, and both methods result in unwanted levels being created which leads to problems when I try to copy or reference certain cells.

Daniel, When Group is entered as a factor, and the factor has two levels, the ANOVA table gives a p value for each level of the factor. What I am looking for is the omnibus p value for the factor, i.e. the test that the factor (with all its levels) improves the prediction of the outcome. You are correct that normally one could rely on the fact that the model

I want to load many files in the R. The names of the files are "Sim1.txt", " Sim2.txt", "Sim3.txt", "Sim4.txt", "Sim5.txt" and so on. Can I read them at one time? What should I do? I can give the same names in R. Thanks. For example: > tst=paste("Sim",1:20,".txt",sep="") # the file names > tst [1]

I have a problem regarding the colors assigned to the lines in the key to an xy plot. I specify the plot like this: xyplot(numbers~sqrt(breaks)|moltype+disttype, groups = type, data = alldata, layout = c(3,2), type = "l" , lwd = 2, col = c("gray", "skyblue"), key = simpleKey(levels(alldata$type), points = FALSE, lines = TRUE, columns = 2, lwd = 2,

Hi everyone and thank you for the help you could give me. My data is in a spreadsheet. The 1st column identifies the firm (with the fiscal number), the columns 2 to 11 have the variable value for 11 years. I have many variables (files like this). Each file has about 40.000 firms (rows). I transformed all the files in txt files. The data is a panel data, like this: firm revenu2007 revenue2006