similar to: creating a contingency table from a data.frame automatically (NOT BY HAND)

Hello! I am doing an analysis on a questionnaire of hunters taken in 4 different districts of some mysterious foreign country. The aim of the study was to gather info on the factors that determine the hunting success of a peculiarly beautiful bird in that area. All variables are factors, i.e. they are variables such as "Use of Guns - yes / no", "Use of Dogs - yes / no" and

Hello, Let's assume I have a vector of integers : > myvector <- c(1, 2, 3, 2, 1, 3, 5) My purpose is to obtain the cumulative distribution of these numerical data, i.e. something like : value nb_occur. <=1 2 <=2 4 <=3 6 <=4 6 <=5 7 For this, I create a table with ; > mytable <- table(myvector) 1 2 3 5 2 2 2 1 However, table() returns an array

Hello! May you help me? I'm trying to do a contingency table using this > data(iris) > library(rpart) > modelo <- rpart(Species ~., iris) > prev <- predict(modelo, iris) Finally the contingency table > table(iris$Species, prev) But an error occurs: Error in table(iris$Species, prev) : all arguments must have the same length And I do not understand why, may you

Dear R-help, We are conducting a distance-based redundancy analysis using capscale and then testing for statistical significance for six terms in the model for the constrained ordination using anova.cca in the vegan package. The significance test is sequential, i.e., testing for significance of a term only after accounting for all preceding terms. Could someone please provide us with either the

Hi R-users! I have the following example: a<-data.frame(cat=c(5,10,15), dog=c(5,10, 15), mouse=c(10,10,20)) b<-data.frame(cat=c(15,10,5), dog=c(15, 10, 5), mouse=c(20,10,10)) rownames(b)<-c("scared", "happy", "sad") rownames(a)<-c("scared", "happy", "sad") Let's say that a and b are 2 contingency tables and 5,10, 15, 20

Ok, before I definetly give up, and throw the laptop out of the window, or fill my data.frame manually, I'll ask for some help. I have a data.frame named MyTable with 3 columns, that looks like this: V1 V2 V3 red-j appearanceblood-n 105.032 red-j appearanceground-n 93.749 red-j appearancesea-n 102.167 red-j appearancesky-n 10.898

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

I'd like to carry out a Monte Carlo simulation test where given data is a contingency table. I think this is something to do with using rmultinonom(), but I'm not sure how to code this, to simulate contingency tables. Could anyone please help with how to use R to simulate contingency tables like this? -- View this message in context:

Hi, my x-axis contains labels that consist of two lines (the actual label and below information about groupsize). Unfortunately, there is too little spacing between labels and tickmarks in this situation. Is there a parameter to tune spacing between axis and labels? Thanks, Chris

hello everyone, i often work on contingency table that I create from data.frame (with table() function) but a friend sent me an excel sheet wich *already is* a contingency table (just a simple 2 way table !...) any clue on how to import it in R (keeping row names and col names) ? any tuto I come accross only mention the table transformation, but never the import of such data I only found

Hi, I have a table in R with data I needed and need to create a contingency table out of it. The table I have so far looks like this: Binger r DietType No Yes Dangerous 15 12 Healthy 52 9 None 134 24 Unhealthy 72 23 These are the error messages that I keep getting whenever I try to get a contingency table. I'm not sure why it won't work

Hi All, I have a question regarding contingency tables. I would like to calculate the mean and standard deviation of a continuous variable from my own dataset based on the percentages of a contingency table I obtained from a scientific article. dataset<- data.frame(cbind(case=rep(0:1,5), x1=c(1:10), x2=c(0:9))) contingency_table<- matrix(c(100, 75, 65, 85, 90, 87), nrow=3, ncol=3) In

How can I draw a 3D perspective of a contingency table, that is showing 3D bars whose height is in proportion of the table cells? --------------- Charles RAUX, Laboratoire d'Economie des Transports CNRS-Universit? Lumi?re Lyon 2-ENTPE email : charles.raux at let.ish-lyon.cnrs.fr http://www.ish-lyon.cnrs.fr/let -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

Is there any existing function for creating contingency tables that will display counts, row, column, and cell percentages in the same tables....anything similar to crosstabs in S? Marc W. Zodet, MS Health Statistician Center for Cost and Financing Studies Division of Statistical Research and Methods 2101 East Jefferson Street, Suite 500 Rockville, Maryland 20852 Phone: 301-594-7072 Fax:

Hi, I post the question again. x<-rep(c(2,3,4),20) y<-sample(rep(c(0,1),30)) tr<-rep(c(1:5),6) data1<-data.frame(x,y,tr) data1<-data1[order(data1$tr),] > data1 x y tr 2 1 1 4 0 1 3 1 1 2 1 1 4 1 1 3 1 1 2 0 1 4 0 1 3 0 1 2 0 1 4 0 1 3 1 1 3 0 2 2 0 2 >table(data1) tr = 1 y x 0 1 2 2 2 3 1 3 4 3 1 tr = 2 y x 0 1 2 2 2 3 2 2 4 1 3

Hello all, Let say I have 2-way contingency table: Tab <- matrix(c(8, 10, 12, 6), nr = 2) and the Chi-squared test could not reject the independence: > chisq.test(Tab) Pearson's Chi-squared test with Yates' continuity correction data: Tab X-squared = 1.0125, df = 1, p-value = 0.3143 However I want to get all possible contingency tables under this independence

I have had the same problem and I wrote this function rmulti <- function(n, size, p) { NrDim <- length(p) if(NrDim<2) stop("The simulated variabel has to be at least 2-dimensional") res <- matrix(data=NA, nrow=n, ncol=NrDim) p <- p/sum(p) TempSize <- size for(i in 1:NrDim) { TempP <- p[i]/sum(p[i:NrDim]) TempBin <- rbinom(n=n, size=TempSize,

Dear all, I have a dataset with qualitative variables (factors) and I want to test the null hypothesis of independance between two variables for each pair by using appropriate tests on contingency tables. I first applied chisq.test and obtained dependance in almost all cases with extremely small p-values and warning messages. > chisq.test(table(data$ins.f, data$ins.st))$p.val [1]

Dear R-philes: I am having an issue with exporting contingency tables with xtable(). I set up a contingency and convert it to a matrix for passing to xtable() as shown below. v.cont.table <- table(v_lda$class, grps, dnn=c("predicted", "observed")) v.cont.mat <- as.matrix(v.cont.table) Both produce output as follows: observed predicted uh uh~ uh 201