similar to: Negating two identical characters with regular expressions

Ciao, ho recentemente acquistato un metodo molto costoso per guadagnare su Internet. Il metodo funziona davvero!!! Ora, in un giorno guadagno pi? denaro di quanto molti ne guadagnano in un mese. Le mie statistiche per oggi. Ho guadagnato _570 in 40 minuti. Fico, vero? Questo metodo funzioner? per circa 2 mesi. Io ho 2 inviti gratis; vorrei condividerne uno con te, solo non dirlo a

Amo le curve femminili, senza avere una particolare predilezione per questo o quel tipo di curva. Per intenderci, il seno mi piace sia che sia piccolo, sia che sia grande. La sensazione al tatto poi ? sempre diversa e foriera di una straordinaria variet? di emozioni. Di quelli piccoli ? bello disegnare il profilo con un dito (solitamente s'inturgidisce subito... mhhh) di quelli grandi mi piace

Hello everyone, does anyone reported similar problems with ess 16.10-1 and R version 3.3.2 RC? These are the steps I do to reproduce it - Open any R script - C-c C-n (or C-c C-j) on any line to start the interactive session - the R process is started but it's hanging and emacs "freeze" (any command is ignored) R version 3.3.2 RC (2016-10-23 r71578) -- "Sincere Pumpkin

Hello, I would like to reorder columns in a data frame by their names as demonstrated below: Take this data frame: > xxx <- data.frame(matrix(1:40, ncol=8)) > names(xxx) <- letters[1:8] > xxx a b c d e f g h 1 1 6 11 16 21 26 31 36 2 2 7 12 17 22 27 32 37 3 3 8 13 18 23 28 33 38 4 4 9 14 19 24 29 34 39 5 5 10 15 20 25 30 35 40 and reorder the columns like

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)

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

First a statistical issue: The survfit routine will produce predicted survival curves for any requested combination of the covariates in the original model. This is not the same thing as an "adjusted" survival curve. Confusion on this is prevalent, however. True adjustment requires a population average over the confounding factors and is closely related to the standardized

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

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)

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).

I have a situation where I''d like to perform some actions when a node is removed from a class. I have a few (homegrown) services that install ssh keys in authorized_keys and it''s possible that a node may have the service enabled and disabled during it''s lifetime. When disabled I''d like to clean up the ssh keys for security reasons. This brings up the broader

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

On 16 Apr 2009, at 11:22, Joaquin Rivera Padron wrote: > at the moment I do it this way, hiding the complexity out of the > steps: > > Then /^I should see the people search form$/ do > people_search_form_exists > end > > Then /^I should not see the people search form$/ do > people_search_form_exists "not" > end > > and then the method: > >

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" ) ,

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 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

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){

Recently there was a question on using lme with large data sets. As an experiment I fit a linear mixed-effects model to a data set with about 350,000 observations on 6 predictors, a numerical response, and a single grouping factor. The timings shown below were on a 1.2 GHz Athlon with 1 GB of PC133 memory and 2 GB of swap. The operating system is Debian 3.0 GNU/Linux. The kernel is 2.4.14.