similar to: Mapping factors to a new set of factors

I have two factors l1, l2, and I'd like to merge them. (Remark: The factors can not be converted to charaters) Function c() does not give me the result I want: > l1 = factor(c('aaaa', 'bbbb')) > l2 = factor(c('ccc', 'dd')) > lMerge = factor(c(l1, l2)) > lMerge [1] 1 2 1 2 Levels: 1 2 > I'd like to merge l1 and l2 and to get lMerge

Hello: Forgive me, this is surely a simple question but I can't figure it out, having consulted the help archives and "Data Manipulation With R" (Spector). I have a list of 11 data frames with one common variable in each (prov). I'd like to use lapply to go through and recode one particular level of that common variable. I can get the recode to work, but it only returns the

Hi! Given a vector (or a factor within a df),i.e. v1 <- c(1,1,1,2,3,4,1,10,3) and a dictionary cbind(c(1,2,3),c(1001,1002,1003)) is there a function (on the same line than recode() in car) to get v2 as c(1001,1001,1001,1002,1003,4,1001,10,1003) ? I'm using myself a function based on match() since long ago (I think that thanks to advice by Prof. B. Ripley), but would like to know if there

I'm working on an R package in C and can't seem to get the same level information about a factor that the R console displays. If I define a factor as: lvls <- factor(c('red','blue','blue','green','red'), c('blue','green','red'), ordered=TRUE) When I get the "levels" attribute in C, I get back the the first

Dear R-ers, I have a data frame data with predictors x1 through x5 and the response variable y. I am running a simple regression: reg<-lm(y~x1, data=data) I would like to loop through all predictors. Something like: predictors<-c("x1","x2",... "x10) for(i in predictors){ reg<-lm(y~i) etc. } But it's not working. I am getting an error: Error in

hi all when i was running ubuntu 8.04 i followed the guide given to install dreamweaver cs3 but now that i have done a fresh install of ubuntu 8.10 when i go to do the recode part it gives me this error: recode: dreamweaver.reg failed: Untranslatable input in step `ISO-10646-UCS-2..ANSI_X3.4-1968' now i am still a new convert to linux and do not know many things, but all i know is that i

Hello, I can get the median for each factor, but I'd like another column to go with each factor. The nm column is a long name for the lvls column. So unique work except for the order can get messed up. Example: x =

I know this comes up, but I didn't see my exact issue in the archives. I have variables in a dataframe that need to be recoded. Here is what I'm dealing with I have a factor called aa > class(aa) [1] "factor" > table(aa) aa * 0 1 2 3 A B C D L N T 0 0 1908 725 2089 0 0 67 0 0 2 1 6 I need to recode

Hi everyone, I'm sure this is pretty basic but I couldn't find a clear example of how to do this. I'm running a regression, say: reg <- lm(Y ~ x1 + year) where x1 is a continuous variable and year is a factor with various year levels. Individually, each year factor variable is not significant, but I have a suspicion they are jointly significant. I can't figure out how to run

I'm having a problem with aggregate.formula when I call it in a function and the function is converted from a string in the funtion I think my problem may also only occur when the left hand side of the formula is cbind(...) Here is example code that generates a dataset and then the error. The first function "agg2" fails > agg2(FALSE) do agg 2 Error in m[[2L]][[2L]] : object

I'm having a bit of trouble recoding factors in a fields. I have a field which has the factors Singleton, Twin and Triplet. I want to recode the field to have only the factors Singleton and Multiple. Any advice? Cheers, Neil

Hi All, I am currently conducting a mixed model. I have 7 repeated measures on a simulated clinical trial. If I understand the model correctly, the outcome is the measure (as a factor) the predictors are clinical group and trial (1-7). The fixed factors are the measure and group. The random factors are the intercept and id and group. I tried using 2 functions to calculate mixed effects.

xtabs does this automatically if your cross classifying variables are factors with levels all the cities (sorted, if you like): > x <- sample(letters[1:5],8, rep=TRUE) > y <- sample(letters[1:5],8,rep=TRUE) > xtabs(~ x + y) y x c d e a 1 0 0 b 0 0 1 c 1 0 0 d 1 1 1 e 1 1 0 > lvls <- sort(union(x,y)) > x <- factor(x, levels = lvls) > y <-

The subject of your email is missing. Perhaps you need to read the Posting Guide (again?) about attachments. Embedding your example directly in the body of the email is generally more accessible in archives than attaching it. -- Sent from my phone. Please excuse my brevity. On April 27, 2016 1:14:17 PM GMT+01:00, G.Maubach at gmx.de wrote: >Hi All, > >I am addressing this post to all

Dear R experts Sorry for this question M1 <- 1:10 lcd1 <- c(11, 22, 33, 44, 11, 22, 33, 33, 22, 11) lcd2 <- c(22, 11, 44, 11, 33, 11, 22, 22, 11, 22) lcd3 <- c(12, 12, 34, 14, 13, 12, 23, 23, 12, 12) #generating variables through sampling pvec <- c("PR1", "PR2", "PR3", "PR4", "PR5", "PR6", "PR7",

Hi All, I am addressing this post to all who are new to R. When learing R in the last weeks I took some notes for myself to have code snippets ready for the data analysis process. I put these snippets together as a script template for future use. Almost all of the given command prototypes are tested. The template script contains snippets for best practices and leaves out the commands that

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

This is probably very simple but I'm new to R so apologies for being stupid. I have some data with No coded as 0 and yes coded as 1. e.g. id sex alcohol smoker 1 M 0 1 2 F 1 0 3 M 0 0 I realise I can covert the numerical variable back to a factor by falcohol<-factor(alcohol,levels=0:1) levels<-c("No","Yes")

I have a data set with seven inputs. Four of which are categorical. For my midterm, my professor wants us to scale all the inputs. This means, I pressume, that I have to use 'recode' or 'factor' to transform the categorical data in numerical. For example, one input variable is 'race=(b,w,h,o)'. I just want to assign a numerical value to all 'b,w,h,o'. I

Dear R helpers, I'm trying to recode an ordered factor to reverse its scale, but I can't figure out how to make it. I am using the Recode function provided by the Car package. I've created an ordered variable: data$o.var1 <- ordered(data$var1, levels=c(1,2,3,4), labels =c("very satisfied", "fairly satisfied", "not very satisfied", "not at all