similar to: Plotting an adjusted survival curve

Dear R-users I am trying to make an adjusted Kaplan-Meier curve (using the Survival package) but I am having difficulty with plotting it so that the plot only shows the curves for the adjusted results. My data come from a randomised controlled trial, and I would like the adjusted Kaplan-Meier curve to only show two curves for the adjusted survival: one for those on treatment (Treatment==1)

Hi, I am currently working to generate selection from my validation table where code and description pairs are stored. This works fine except when the current value is not exist in validation table. There are some old data which contains values that are no longer used and not in my validation table. I do not want to add old values in my validation table; however, I would like to display these

Two things I think are some of the best developments in statistics and production are the lattice package and the beamer class for presentation in Latex. One thing I have not become very good at is properly sizing my visuals to look good in a presentation. For instance, I have the following code that creates a nice plot (sorry, cannot provide reproducible data).

Hello all, Let's say I have a character string "Race-ethnicity-----coding information" I want to extract all text before the multiple dashes, including the word "ethnicity." I wrote a handy function to extract the first matched text: grepcut <- function(pattern,x){ start.and.length <- regexpr(pattern,x) substring(x,start.and.length,start.and.length

Dear friends, I am trying to understand and implement instrumental variables regression using R. I found a small (simple) example here which purportedly illustrates the mechanics (using 2-stage least-squares): http://www.r-bloggers.com/a-simple-instrumental-variables-problem/ Basically, here are the R commands (reproducible example) from that site: # ------ begin R library(AER)

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" ) ,

Hi, I have the following data management issue. I am trying to combine multiple years of ethnicity data into one variable called ethnic. The data looks similar to the following id ethnic07 ethnic08 ethnic09 ethnic10 1 1 1 1 1 2 1 1 2 2 3 3 4 4

I had occasion recently to read in a one-line *.csv file that looked like: "CandidateName","NSN","Ethnicity","dob","gender" "Smith, Mary Jane",111222333,"E","2/25/1989","F" That "F" (for female) in the last field got transformed to FALSE. Apparently read.csv (and hence read.table) are inferring

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

Hi All, The data set that I have is a cluster data, and I want to run a HLM mixed model with multi-level response. Here is my data set: response: - Level (num: 1, 2, 3, 4, 5 - 5 levels) Covariates: - Type (Factor: A, B, C - 3 levels) - yr (num: 2006, 2007, ...) - Male (num: 0=not Male, 1=Male - 2 levels) - Ethnicity (Factor: A, B, H, ..., - 7 levels) - ELL (num: 0, 1, - 2

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){

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

I'd like to thank John Fox and Chuck Cleland for their help in resovling this issue. It turned out to be something simple, but perhaps others have had similar problems In my original data frame, I had 4 categories of race/ethnicity. One of the categories (other) was very small, and not similar to any of the other three categories, so I created a new data frame deleting those people.

On 13 October 2015 at 16:41, Rafael Espíndola <llvm-dev at lists.llvm.org> wrote: >> - *Be welcoming.* We strive to be a community that welcomes and supports >> people of all backgrounds and identities. This includes, but is not limited >> to members of any race, ethnicity, culture, national origin, colour, >> immigration status, social and economic class, educational

Hola, Tengo un tabla de datos con pacientes asistidos, para los cuáles tengo variables como dni, género, programa de atención etc. Hay pacientes que atendieron en más de un programa por lo cuál se repiten en la tabla. Lo que quiero es poder contar con una matriz que me permita identificar la cantidad de pacientes que coinciden entre programas. Va un ejemplo: [image: image.png] Intenté de

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

I'm trying to figure out how to use lmer to fit models with factors that have some nesting and some non-nested groupings. For example, in this paper: http://www.stat.columbia.edu/~gelman/research/published/parkgelmanbafumi.pdf we have a logistic regression of survey respondents' political preferences (1=Republican, 0=Democrat), regressing on sex, ethnicity, state (51 states within 5

On Sat, Oct 17, 2015 at 8:24 PM, Pasi Parviainen via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On 14.10.2015 23:36, Chandler Carruth via llvm-dev wrote: > >> * **Be welcoming.** We strive to be a community that welcomes and supports >> people of all backgrounds and identities. This includes, but is not >> limited >> to members of any race,

Dear users of metafor, I am working on a meta-analysis using the metafor package. I have a excel csv database that I am working with. I am interested in pooling the effect measures for a particular subgroup (European women) in this csv database. I am conducting both sub-group and meta-regression. In subgroup-analyses, I have stratified the database to create a separate csv file just for European

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