search for: idvars

Hi R users, I have a test dataframe ("file1," shown below) for which I am trying to create a flag for the first and last ID record (equivalent to SAS first.id and last.id variables. Dump of file1: > file1 id rx week dv1 1 1 1 1 1 2 1 1 2 1 3 1 1 3 2 4 2 1 1 3 5 2 1 2 4 6 2 1 3 1 7 3 1 1 2 8 3 1 2 3 9 3 1 3

Suppose I have the following function myFun <- function(formula, data){ f <- formula(formula) dat <- model.frame(f, data) dat } Applying it with this sample data yields a new dataframe: qqq <- data.frame(grade = c(3, NA, 3,4,5,5,4,3), score = rnorm(8), idVar = c(1:8)) dat <- myFun(score ~ grade, qqq) However, what I would like is for the resulting dataframe (dat) to include

Hello everybody, I have been recently using reshape to convert "long" data to "wide" data. Everything was going well until I reached some problematic datasets. It has taken me a couple of weeks to finally figure out what might be happening. The problem is reproducible with test cases, and on two versions of R (Windows 2.2.0 and x86-64 Fedora Core 3 R 2.2.0). The data

All, I am using the forestplot function in rmeta. I was able to modify the x axis range by commenting out one line and feeding it two new parameters (I wanted to set zero as the axis start point). #xrange <- c(max(min(lower, na.rm = TRUE), clip[1]), min(max(upper, na.rm = TRUE), clip[2])) #new line xrange <- c(xlow,xhigh) Now I am trying to modify the text font size for

Full_Name: Kevin Wright Version: 1.4 OS: Windows 95 Submission from: (NULL) (170.54.59.160) Note: This was the 1.4 build for Windows that Brian Ripley made available. The first example in the help for reshape doesn't work for me. When I cut and paste, this is what happens: > data(Indometh,package="nls") > summary(Indometh) Subject time conc

Hello * I would like to reshape wide the following dataset: > rl <- read.dta("intermedi/rapporti_lavoro.dta") [c("id_rl","prog","sil_pi","sil_cf","sil_dat_avv")] > dim(rl) [1] 12964 5 > object.size(rl) 1194728 bytes > head(rl) id_rl prog sil_pi sil_cf sil_dat_avv 1 638 1 04567XXXXXX

Hello, I am trying to wrap some code that I repeatedly use into a function for efficiency. The following is a toy example simply to illustrate the problem. foobar.fun<-function(data,idvar,dv){ id.list<-unique(idvar) result<-numeric(0) for (i in id.list){ tmp1<-subset(data, idvar == i) result[i]<-mean(get("tmp1")[[dv]]) } return(result) } The

I want to fit a series of lme() regression models that differ only in the degrees of freedom of a ns() spline. I want to use a wrapper function to do this. The models will be of the form y ~ ns(x, df=splineDF) where splineDF is passed as an argument to a wrapper function. This works fine if the regression function is lm(). But with lme(), I get an error. fitfunction() below demonstrates this.

Salutations: I have been trying to translate a S-PLUS/ArcInfo (GIS software) application that I wrote on a SGI (IRIX) platform to public domain R and GrassGIS on a Linux platform. I am almost on the verge of abandoning it as I find R to be rather unstable, slow and frustrating. I enclose a section of my code for R experts to examine hoping that they'll point out that all the above three are

Folks, I am holding a dataset where firms are observed for a fixed (and small) set of years. The data is in "long" format - one record for one firm for one point in time. A state variable is observed (a factor). I wish to make a markov transition matrix about the time-series evolution of that state variable. The code below does this. But it's hardcoded to the specific years that I

Dear R Community, I am attempting to transpose a dataset from rows to columns but am stuck. I have tried using reshape() with little luck, possibly due to the categorical nature of the data. For example: id<-c(1,2,2,3,3,3) author<-c("j","k","k","l","l","l")

I would appreciate some advice on the following task. I have some data that currently looks like this: t1 <- data.frame(id=c(1,1,2,2), aspect=c("A","B","A","B"), score=c(10,9,11,12)) I'd like it to look like this: id A B 1 10 9 2 11 12 reshape() looks like a good candidate for this job but I'm not really sure about the roles of

...CET"). Now, I want to sort the data frame in ascending order by a, b, c and then in descending order by t. Here's what I've got, but I'm not sure how to put the 'descending' bit in the code. The trick with the minus sign doesn't work as the var isn't numeric. idvars <-- c("a", "b", "c") myData["t"] <- as.POSIXct(myData[,"t"]) result <- myData[ do.call(order, myData[c(idvars, "t")]), ] This should be simple, I guess, but I've been staring at this a bit too long now. Suggestions anyone? T...

I solved the problem in one more (and more elegant) way. So here's the program again. Where does R stand on the Anderson-Goodman test of 1957? I hunted around and nobody seems to be doing this in R. Is it that there has been much progress after 1957 and nobody uses it anymore? # Problem statement: # # You are holding a dataset where firms are observed for a fixed # (and small) set of years.

Hi, Try ?unique() You haven't provided reproducible data or information about the package.? So, this may or may not work. dat1<- data.frame(idvar=c(rep(1,2),2,4),col2=c(7,7,8,9)) ?dat1 #? idvar col2 #1???? 1??? 7 #2???? 1??? 7 #3???? 2??? 8 #4???? 4??? 9 ?unique(dat1) #? idvar col2 #1???? 1??? 7 #3???? 2??? 8 #4???? 4??? 9 A.K. I got the following message when trying to use Google

Full_Name: Alexander L. Belikoff Version: 2.8.1 OS: Ubuntu 9.04 (x86_64) Submission from: (NULL) (67.244.71.200) I'm trying to reshape the following data frame: ID DATE1 DATE2 VALUE_TYPE VALUE 'abcd1233' 2009-11-12 2009-12-23 'TYPE1' 123.45 ... VALUE_TYPE is a string and is a factor with only 2 values

...but only when openblas stuff is in the picture. I wondered what you think? Here's the code to reproduce this: datM <- read.csv("http://pj.freefaculty.org/scraps/profile/missingDat.csv") library(Amelia) set.seed(12345) Rprof("Amelia-1.out") impA <- amelia(datM, m = 5, idvars="group") Rprof(NULL) summaryRprof("Amelia-1.out") Here's the crashed session > datM <- read.csv("http://pj.freefaculty.org/scraps/profile/missingDat.csv") > library(Amelia) Loading required package: foreign ## ## Amelia II: Multiple Imputation ## (Versi...

Hi all: I solved the previous stated problem in something of a brute force way (but it works). I seem to now be running into one little hiccup using reshape. Here is a quick snip of the data in long format: grade stability year schid 6 Grade 4 3 2001 100005 7 Grade 4 3 2002 100005 8 Grade 4 2 2003 100005 10 Grade 5 2 2001 100005 11 Grade 5

Hi, It's probably a simple issue but I'm struggling with that. I'll use the example shown in the help page. head(Indometh) wide <- reshape(Indometh, v.names="conc", idvar="Subject", timevar="time", direction="wide") head(wide) reshape(wide, idvar="Subject", varying=list(2:12), v.names="conc",

...nth, measurements, standard deviation of the measurement). Of course, there are some random missing values on columns 3 and 4. The measurements are an almost periodic time-series contaminated by noise. I did some tests such as: a.out <- amelia(x, m = 5, ts = "YEAR", p2s = 0, idvars=c("DEV")); > a.out <- amelia(x, m = 5, ts = "YEAR", p2s = 0, idvars=c("MON","DEV")); Error in matrix(1, AMn, 1) : non-numeric matrix extent a.out <- amelia(x, m = 5, ts = "YEAR", p2s = 0); a.out <- amelia(x, m = 5, p2s = 0, idv...