similar to: R crashing during batch file formatting

Do any of you know any simple programming editors for R scripts which offer basic colour-coding and bracket-matching facilities? Dregging through scripts to find a missing comma or parentheses is something I'd rather do less of... Jon Minton [[alternative HTML version deleted]]

Dear R users: Is there a built-in and simple way to insert new columns after other columns in a dataframe? I.e. currently I have: V1 V2 V3 V4 [1,] [2,] Etc. But I want V1 V5 V2 V3 V4 [1,] [2,] Etc. Can this be done in one line? Jon Minton [[alternative HTML version deleted]]

Hi, apologies if this is too simple but I've been stuck on the following for a while: I have a vector of strings: filenames with a name before the extension and a variety of possible extensions I want to select only those files with: 1) a ".tab" extension AND 2) the character sequence "lad" anywhere in the name of the file before the extension. Surely this

Hello, I have a dataframe containing the following variables: PID, Field, Value Where PID refers to a unique individual, Field to a particular question, and Value to a particular response to a question. I?d like this in wide format, with a different row for each PID. However.... there are differing numbers of Values associated with each Field, for each PID. For example, a Field question may

Hi: Do any of you know if there's an equivalent function to the Stata command: Use v1 v3 v5 v2 v7 using file.dat In R? (i.e. something that just selectively loads certain variables from a file and not others)? Thanks Jon Minton [[alternative HTML version deleted]]

This is probably very simple but my brain has frozen over. (I'm trying to warm it with coffee) I have observations of around 22000 individuals over 13 successive years: they were either 'interviewed' at time t or 'not interviewed'. What's the most appropriate function/approach to use to find out the extent to which individuals' event outcomes are temporally

Hi, I have a set of dataframes names AINDSLIM, BINDSLIM, CINDSLIM ... NINDSLIM In each dataframe I want to extract two variables, “pid” and “{w}region”, where {w} means “a”, “b”, “c”, ...”n” At the moment my code looks like: > PidRegion <- data.frame(pid=XWAVEID$pid) > this.region <- AINDSLIM[,c("pid", "aregion")] > PidRegion <- merge(PidRegion,

Dear R Users, Do you know of an existing function that allows the production of sensitivity and specificity forest plots? See the following for an example:

Hi, I expect this is simple but haven’t found an answer looking on the archives... I want to convert ‘NA’ (missing) to particular levels (nonmissing) in factor vectors. e.g. I know > X <- c(1, 2, 3) > summary(X) Min. 1st Qu. Median Mean 3rd Qu. Max. 1.0 1.5 2.0 2.0 2.5 3.0 > X <- as.factor(X) > summary(X) 1 2 3 1 1 1 >

Hi everyone, Does anyone here has experience using MICE to impute missing value? I am having problem to pool the imputed dataset for a MANOVA test, could you give me some advice please? Here is my code: > library(mice) >

Hi, in the code below, I am drawing 1000 samples from two beta distributions, each time using the same random number seed. Using set.seed(80) produces results I expect, in that the differences between the distributions are very small. Using set.seed(20) produces results I can't make sense of. Around half of the time, it behaves as with set.seed(80), but around half of the time, it behaves

Dear R-Help List, I'm trying to implement Firth's (1993) bias correction for log-linear models. Firth (1993) states that such a correction can be implemented by supplementing the data with a function of h_i, the diagonals from the hat matrix, but doesn't provide further details. I can see that for a saturated log-linear model, h_i=1 for all i, hence one just adds 1/2 to each count,

I am working with some survival data with missing values. I am using the mice package to do multiple imputation. I have found code in this thread which handles pooling of the MI results: https://stat.ethz.ch/pipermail/r-help/2007-May/132180.html Now I would like to plot a survival curve using the pooled results. Here is a reproducible example: require(survival) require(mice) set.seed(2) dt

Hi, I'm new to R so this might be a little basic for enlightened people like yourselves... I have quarterly British Labour Force Survey (Local Area) data from 1992 to present in .tab format* in folders running from 01 (for the first time period) to 56 (for the most recent). i.e. my directory structure is: .../t/ 01 ... 56

Hello Running R2.9.2 on Windows XP I am puzzled by the performance of LME in situations where there are missing data. As I understand it, one of the strengths of this sort of model is how well it deals with missing data, yet lme requires nonmissing data. Thus, m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_, data = long, random =

The Toolkit for Weighting and Analysis of Nonequivalent Groups (twang 1.0) has been released to CRAN. The package collects functions useful for computing propensity score weights for treatment effect estimation, developing nonresponse weights, and diagnosing the quality of those weights. The package includes a vignette containing some basic theory and walks through two examples. It is available by

Dear All, A few weeks ago I posted a question to this list but unfortunately got no answer! A friend warned me of my english. Again, the problem is: A 2-level 5-factors completely randomized design was used to investigate the potential effects of those factors on a solution's characters (several response variables). Each response-variable was measured repeatedly (13 times) during a

Hello all, why I can run whis command: imap1:~ # doveadm user user001 userdb: user001 ? mail????? : maildir:/var/maildir/vol04/4/46/user001 ? home????? : /var/mailfilter/vol04/4/46/user001 ? quota_rule: *:bytes=100000000 but not this one: imap1:~ # doveadm quota get -u user001 doveadm(user001): Error: user user001: Auth PASS lookup failed doveadm(user001): Fatal: passdb lookup failed what

We're looking for one or more technical people at varying levels for our group at YouGov. See below for the job descriptions. Feel free to email me directly with questions. ------- YouGov is seeking two technically sophisticated persons for its Innovations Group, based in Redwood City. We are looking for people who combine knowledge of applied statistics or econometrics with strong

Hi I have used the amelia command from the Amelia R package. this gives me a number of imputed datasets. This may be a silly question, but i am not a statistician, but I am not sure how to combine these results to obtain the imputed dataset to usse for further statistical analysis. I have looked through the amelia and zelig manuals but still can not find the answer. This maybe because I dont