similar to: Tabulating using arbitrary numbers of factors

[[1]]              [,1]      [,2] [1,]  0.003632559 0.2190629 [2,] -2.090772847 0.2190629 [[2]]             [,1]       [,2] [1,] 0.004278991 0.04337005 [2,] 0.190723602 0.04337005 [[3]]            [,1]        [,2] [1,] 0.01237827 -0.01544811 [2,] 0.06452200 -0.01544811 g<-c(1,2,3) function(g,hessianList){    for(i in 1:3){          ft1<-g[2]*hessianList[[2]]          ft2<-sum(ft1)   

Dear R Users: I have race-ethnicity groups identified in the factor variable Ethnic_G. I need to collapse Ethnic_G into a new variable with only two factors, 1 (White, non-Hispanic) and 2 (Minority). As seen in the code and output below, the recoded race-ethnicity variable is put into logical format, not factor format. I've used library(car) and the package was updated. Any ideas on

Hello--I'm doing a simple crosstab using dcast: rawfreq <- dcast(nh11brfs, race3~CHCCOPD, length) with the results race3 Yes No NA 1 White non-Hispanic 446 5473 21 2 Other non-Hispanic 29 211 0 3 Hispanic 6 81 1 4 <NA> 10 83 1 How would I modify this call to exclude all missing values; that is, to obtain race3

Hello, I have compiled and installed (almost) wine 0.9.24 within Mac OS X tiger 4.8 with X11 etc installed. The wine configure and compile steps complete without a warning/hitch etc. However, when I run wine <prog> I receive the following warning message -- Wine cannot find the FreeType font library. To enable Wine to use True Type fonts please install a version of FreeType greater

Buenas tardes, Quiero aplicar la función rbind y necesito tener los mismos nombres de columnas. Como tengo unas 195 variables en cada dataframe, necesito hacerlo de una forma rápida. Tengo 9 bases de datos y tengo que fusionar todas. ¿Como puedo comprobar que los nombres de las variables son los mismos? Y de lo contrario, ¿como detecto las diferencias? He probado con

Newbie here. Many apologies in advance for using the incorrect lingo. I'm new to statistics and VERY new to R. I'm attempting to "group" or "bin" data together in order to analyze them as a combined group rather than as discrete set. I'll provide a simple example of the data for illustrative purposes. Patient ID | Charges | Age | Race 1 |

HI, Dear R community, I am using the xtable to create the table, but how can I see the table? The following is the codes I used: > data(tli) > tli.table <- xtable(tli[1:10, ]) > digits(tli.table)[c(2, 6)] <- 0 > print(tli.table, floating = FALSE) % latex table generated in R 2.11.0 by xtable 1.5-6 package % Thu Jul 1 20:43:43 2010 \begin{tabular}{rrlllr} \hline &

I have a function (see below) that does some bootstrapping (I am happy to expand offline why I could use existing functions.) I put my results into and empty matrix and add a row of results with each iteration. My problem is i am a new user to R and I don't understand data frames, matrices, elements, and vectors well. What I would like is to have a data frame I can manipulate outside of the

Hi all, When I try the following with pkg Survey it returns the error below: ftable(svyby(~INCOME, ~AGECL+RACECL, svymean, design=q50), rownames=list(AGECL=c("<35", "35-44", "45-54", "55-64", "65-74", ">=75"), RACECL=c("white non hispanic", "non white or

I am trying to read an ftable using read.ftable, but I get the following error message: > jobSatTable <- read.ftable("http://definetti.uark.edu/~gpetris/stat5333/jobSatisfaction.dat",skip=2) Error in seek(file, where = 0) : no applicable method for "seek" In addition: Warning messages: 1: no non-missing arguments to max; returning -Inf 2: no non-missing arguments to

Hi, I am new to R. My problem is with the ordered logistic model. Here is my question: Generate an order discrete variable using the variable wrwage1 = wages in first full calendar quarter after benefit application in the following way: * wage*1*Ordered *= 1 *if*0 *· wrwage*1 *< *1000 2 *if*1000 *· wrwage*1 *< *2000 3 *if*2000 *· wrwage*1 *< *3000 4 *if*3000 *· wrwage*1 *<

Hi R-ers: I'm drawing a plot and have used different line types (lty) for different race/ethnicity groups. I want a legend that explains what line types correspond to the different race/ethnicity groups. I used the following code: legend( 1992 , 42 , c("Hispanic" , "non-Hispanic white (NHW)" , "non-Hispanic black" , "AI/AN" , "Asian" ) ,

Hello, I'm trying to run a loop that will subset my data into specific sets by regions and by race/ethnicity. I'm trying to do this fairly compactly, and I cannot get this to work. A "simple" version of the code that I am trying to run is: names <- c("white", "black", "asian", "hispanic") for(j in names){ for(i in 1:9){

try resetting your factor levels and re-run? q50 <- update( q50 , INCOME = factor( INCOME ) , AGECL = factor( AGECL ) , RACECL = factor( RACECL ) ) On Sun, Jul 9, 2017 at 2:59 PM, Orsola Costantini via R-help < r-help at r-project.org> wrote: > Hi all, > > When I try the following with pkg Survey it returns the error below: > > ftable(svyby(~INCOME, ~AGECL+RACECL,

I am trying to use tree to partition a data set. The data set has 3924 observations. Partitioning seems to work for small subsets of the data, but when I use the entire data set, no partitioning occurs. The variables are: RESP respondent to a survey (0 = not a respondent, 1 = respondent) AGE_P Age (continuous) ORIGIN_I Hispanic Ethnicity (1 = Hispanic, 2 = non-Hispanic) RACRECI2 Race

hello there, Is there a way of truncating in the opposite direction so as to retain only the values to the right of the decimal?? i.e. rather than: > trunc(39.5) [1] 39 i would get something like: > revtrunc(39.5) [1] 0.5 I've been searching to no avail but I imagine there is a very simple solution! Tyler -- View this message in context:

Hello, I am fitting a gmler using poisson, and I was looking for a documentation to interpret correctly the output. I'm quite a beginner with these kind of models. I couldn't find something in the lme4 package manual. and on the internet neither... Thank you, Raphaelle -- View this message in context: http://www.nabble.com/glmer-documentation-tp21506036p21506036.html Sent from the R

Hello, I have a couple questions regarding generalized linear mixed models specifically around fitting the random effects terms correctly to account for any pseudo-replication. I am reading through and trying to follow examples from Zuur et al. Mixed Effects Models and Extensions in Ecology with R, but am still at bit unsure if I am specifying the models correctly. Background information: Our

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HI there, i know this is a basic question, though i need some help because this is somewhat away from my current issue, but nevertheless interesting to me... Lets assume i have some estimated probabilities, say estimated by a logit model. i know i can also state them as an odds ratio. Now i?d like to state these odds ratios as a reference to a specific outcome of my investigated