similar to: format of 2x2 table

Dear all, I'm trying to create a virtual S4 class with some subclasses. I noticed that adding slots to this class increases the memory use and slows the functions down. Note that I'm adding very small slots (integer or character both of length 1). I've made a reproducible example at https://github.com/ThierryO/testvirtualclass. The R CMD check --as-cran fails on the tests. Some of

I am attempting to produce crosstabulations between two variables for subgroups defined by a third factor variable. I'm using by() and CrossTable() in package gmodels. I get the printing of the tables first and then a printing of each level of the INDICES. For example: library(gmodels) by(warpbreaks, warpbreaks$tension, function(x){CrossTable(x$wool, x$breaks > 30,

I hesitate to post this question in the light of recent threads, indeed I have hesitated for several weeks, however I have come to a full stop and really need some help if I am going to progress. I am a new user of R for medical statistics. I have attempted to read all the relevant documents, but would welcome any suggestions as to what I have missed. I am trying to contruct "table 1"

** Disclaimer: I'm looking for general suggestions ** I'm sorry, but can't send out the file I'm using, so there is no reproducible example. I'm using read.table and it's taking over 30 seconds to read a tiny file. The strange thing is that it takes roughly the same amount of time if the file is 100 times larger. After re-reviewing the data Import / Export manual I think

I am having trouble generating a graph. I want to know the % of respondents who answered that they "strongly agree" or "agree" the "America owes R's ethnic group a better chance" (BTTRCHNC) and I want to organize it by racial group (RACESHRT). "BTTRCHNC" is organized ordinally from 1 through 5 with 1=Strongly Agree, 5=Strongly Disagree

Good evening R-users! I have the following problem: i want to get a weighted crosstable along with the adjusted standardized residuals test Example: a<-c(1,1,1,1,1,2,2,2,3,3) b<-c(10,10,23,24,33,45,46,70,21,66) c<-c(3,3,2,3,4,1,1,1,3,3) d<-c("a", "b","b","c","a","a","a", "b",

# Dear list, # I am an R-beginner and # spent the last days looking for a method to insert tables produced # with R into a word document. I thought about SPPS: copy a table from # an SPO-file and paste it into a word document # (if needed do some formatting with that table). # Annother idea was, to produce a TEX-file, # insert it and make it a word-table. # I found the following libraries, which

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A question about comparing symptom reduction over time and across treatment groups. Each respondent is asked twice if they experience symptoms (coded 1), at baseline and then at 6 months later. They are randomly assigned to either the control or the intervention group. The 2x2x2 table below shows the frequency counts. As can be seen in the margins of the table, 21% of the control group

hi, i'm new in R and i need some help. Please, ¿do you know a function how can process cross tables for many variables and show the result in one table who look like this?: +----------------------------------------------------+ |------------------ | X variable | |----------------- | Xop1 | Xop2 | Xop3|.....| +----------------------------------------------------+ |Yvar1 |

Hello, This is about the new "line profiling" feature in R 3.0.0. As I was testing it, I find the results somewhat disappointing so I'd like to get your opinion. I put some poorly written code in a test.R file, here are the contents: double <- function(x) { out <- c() for (i in x) { out <- c(out, 2*i) # line 4 } return(out) } Then this how I source the file

Is the code below showing a bug in Crosstable()? My expectation was that the values produced by xtabs were rounded instead of truncated: library(gmodels) abc <- c("a", "a", "b", "b", "c", "c") def <- c("d", "e", "f", "f", "d", "e") wgt <- c(0.8, 0.6, 0.4, 0.5, 1.4, 1.3)

Hi, I am using the CrossTable function from library(gmodels). x=unique(data[,c("L1","L1_Revenues","RIC")]) L1_Classification=CrossTable(x$L1,x$L1_Revenues,exclude = c("NA","","0%","0"),prop.r=FALSE,prop.c=FALSE,prop.t=FALSE,prop.chisq=FA LSE,dnn=c("L1_Classification","Revenue")) What I would like

There are too many arguments in the signature of the my_inla generic. The signature defaults to every argument in the formals, which are probably already over-specified. Typically, one defines a generic with the formals (x, ...), or perhaps in this case (x, model, ...), but more on that below Unrelated to this issue, the my_inla generic is defined incorrectly. It should call

Hi, I've been trying to prepare some crosstables for some survey questions for a client. I have been using the CrossTable function in the gmodels package. However, this command only seems to be able to create CrossTables in text documents. I've been trying to use odfTable in odfweave to create tables that are standalone objects in the document that I can then convert to other

Hi R-users, I have the following problem with CrossTable function within ?gmodels? package: the output of the function (format ?spss? and asresid=T) can not be stored within another object. For example: >library(gmodels) >data(infert, package = "datasets") > CrossTable(infert$education, infert$induced)->aa # the function prints everything ok on the screen > aa # works

I have some trouble interpreting the output from profiling. I have read the help pages Rprof, summaryRprof and consult the R extensions manual, but I still have problems understanding the output. Basically the output consist of self.time and total.time. I have the understanding that total.time is the time spent in a given function including any subcalls or child functions or whatever the

Library gmodels include a function CrossTable that is useful for crosstabulation. In the help, it is indicated that one can call this function as CrossTable(data), were data is a matrix. However, when I try to use this option, it doesn't help. Any idea? Is there a bug? Thanks for your help. Prof. Albert Sorribas Grup de Biomatem?tica i Bioestad?stica Departament de Ci?ncies M?diques B?siques

Dear All, I regularly want to "apply" some function to an array in a way that the arguments to the user function depend on the index on which the apply is working. A simple example is: A <- array( runif(160), dim=c(5,4,8) ) x <- matrix( runif(32), nrow=4, ncol=8 ) b <- runif(8) f1 <- function( A, x, b ) { sum( A %*% x ) + b } result <- rep(0.0,8) for (i in 1:8) {

Hello. I asked before and it was great, cause as a beginner I learned a lot. But, if I have this in R (1 and 2 are codes for sex): > sex<-c(1,2,2,1,1,2,2,2) > sex [1] 1 2 2 1 1 2 2 2 I´d like to obtain the proportion according to sex.So I type: > prop.table(sex) [1] 0.07692308 0.15384615 0.15384615 0.07692308 0.07692308 0.15384615 0.15384615 [8] 0.15384615 The result is OK, but I