similar to: Returning Data Frame from Function for use Outside Function

I apologize if this has been answered. I have researched this to the best of my ability, that's not to say the answer isn't in the archives just I am a new user and I don't know the proper terms to search under. I have an object: f <- mpr100 ~ time + nhb + hispanic + other + rural + hrural + factor(age) + factor(gender) +

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

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 |

Hello! I have written an R script on a Windows platform where I calculate eight result matrices I plot using matplot. I would like to display the resulting plots successively, rather than simultaneously, and I was wondering if anyone could point me in the right direction as to how to do this. The graphs pop up in this manner by default when I run my script in S-PLUS, with tabs separating them so I

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 &

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

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 *<

Dear R-help, First of all, thank you VERY much for any help you have time to offer. I greatly appreciate it. I would like to write a function that, given an arbitrary number of factors from a data frame, tabulates the number of occurrences of each unique combination of the factors. Cleary, this works: > table(horse,date,surface) <SNIP> , , surface = TURF

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

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

I just started using R and I'm having all sorts of "fun" trying different things. I'm going to document the different things I'm doing here as a kind of case study. I'm hoping that I'll get help from the community so that I can use R properly. Anyways, in this study, I have demographic data, drug usage data, and side effect data. All of this is loaded into a csv

UseRs, I have a dataframe with 2547 rows and several hundred columns in R 3.1.3. I am trying to run a small logistic regression with a subset of the data. know_fin ~ comp_grp2+age+gender+education+employment+income+ideol+home_lot+home+county > str(knowf3) 'data.frame': 2033 obs. of 18 variables: $ userid : Factor w/ 2542 levels

I have a factor vector of subject races (Asian, Black, Hispanic, White; n=30) that I want to plot with a Cleveland dotplot or dotchart. I tried the following in R2.12.1 : > dotchart(table(school$Race)) Error in plot.xy(xy.coords(x, y), type = type, ...) : invalid plot type Using the same data set in R2.11.1 the operation succeeded (I tried several variations to be sure): >

Michael, Thank you for the suggestion. I will take your advice and look more critically at the covariates. John On 7/27/2017 8:08 AM, Michael Friendly wrote: > Rather than go to a penalized GLM, you might be better off > investigating the sources of quasi-perfect separation and simplifying > the model to avoid or reduce it. In your data set you have several > factors with large

I'm uncertain if this is perhaps a stupid question: I want to create "centered" dummy variables to use in a call to glm(), and wondering if there's some slick method in R to do so. That is, rather than have a factor, which results in a glm() fit returning coefficients specifying either absence or presence of the factor, I'd like to fit a glm() without intercept such that