similar to: S function crosstabs

Hi all! What is the equivalent R function of SPLUS crosstabs? Thank you. Danar. Stat. Inst. Umea Univ. Umea, Sweden -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

Hi, In Splus if I call the function crosstabs() the output is a contigency table; in each cell of the table is printed: N, N/RowTotal, N/ColTotal, N/Total. N is the number of observations in each cell. The same call to xtabs() in R will produce the contigency table but the only entry in each cell is N. How can I get the same relative frequencies that crosstabs() gives? Thanks, mike --

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:

Before I reinvent the wheel, I have need for a relatively straightforward crosstabulation (2 x n) function. I know that R has table(), ftable(), xtabs(), and summary(xtabs()), but none of these produce a fully "tricked" out cross-tabulation with marginal totals, expected cell frequencies, and an array of statistics about the contingency table. Is there a more complete (something

Is there a crosstabs function like the one found in S-Plus available in any of the R addon packages? I can't seem to locate anything other than the chisq.test, which is adequate but does not yield the output customarily required with any journal submission (in my field). (S-Plus, SPSS, SAS all provide examples of the required output). If there isn't such a function already

Is there an equivalent in R to the crosstabs command S-Plus? I've been searching for a while and can't seem to find anything. Thanks. Mark J. Lamias Department of Statistics Department of Political Science Survey Methodology Program/Survey Research Center Institute for Social Research - University of Michigan 426 Thompson Street, Room 315 Ann Arbor, Michigan 48104-2321 (734) 647-5381

Hi, I'm using R version 1.8.0 on Windows NT. When fitting a glm with Poisson random component and a log link, I frequently need to include an offset. Typically I use xtabs or table to get the counts for the contingency table, and then I use as.data.frame.table to create a data frame that I can use in the glm function. I have not found an option that allows me to total the offset variable to

I'm running 1.9.1 on Mac OS X 10.1. My simple question is whether there is a crosstabs-like command (I know about "xtabs" which is much like "table") that computes not only cell counts but also row, column, and cell percents. Something like crosstabs(~x+y) in S-PLUS. Thank you.

Hi, I'm a new R user. I noticed that RKWard has a really nice output when it does crosstabs. It even includes the chi-squared values. However, I obviously can't simply copy this into my standalone R script. Does anyone know the code or a way for me to view the code. Secondly, if I am writing an R script I want to be able to view the output as a pdf even if my function is not a graph,

{again a message that was sent to owner-r-help (which is me, currently) why on earth ???!??!? reply to R-help or the original sender Brett Presnell; } I'm teaching a categorical data analysis course this term, and a minor "problem" has resurfaced that I have often thought about before. This applies equally to Splus I suppose, but my undergrads aren't using Splus. It

Hello all,, Im looking for a simple function to produce a crosstab from a dumped sql query result. Its very hard to produce crosstabs with most databases (Access being the exception), so with the vast array of R packages, Im sure this has to have already been implemented somewhere. Examples are always good: Take a csv dump like name code user1 100 user2 100 user1 200 user2 210 user1 300 user2

Dear Friends. I am just starting to use R. And in this occasion I want to construct a high-dimensional contingency table, because I want to crate a mosaic plot with the vcd package. My table is in this format: año ac.rep cat.gru conteos 1 2005 R parejas 253 2 2005 N parejas 23 3 2006 R parejas 347 4 2006 N parejas 39 5 2007 R

Dear List, I would appreciate help on the following matter: I am aware that higher dimensional contingency tables can be analysed using either log-linear models or as a poisson regression using a generalized linear model: log-linear: loglm(~Age+Site, data=xtabs(~Age+Site, data=SSites.Rev, drop.unused.levels=T)) GLM: glm.table <- as.data.frame(xtabs(~Age+Site, data=SSites.Rev,

I know this is something simple that I cannot do because I do not yet "think" in R. I have a data frame has a variable participation (a factor), and several other factors. I want a chisq test (no contingency tables) for participation vs all of the other factors. In SPSS I would do: CROSSTABS /TABLES= (my other factors) BY participation /FORMAT=NOTABLES /STATISTICS=CHISQ

Hi R users I have serveral binary variables (e.g., X1, X2, X3, X4, X5, X,6, and X7) and one continuous variable (e.g., Y1). I combined these variables using data.frame() mydata <- data.frame(X1,X2,X3,X4,X5,X6,X7,Y1) after that, I sorted this data.frame rank.by.Y1<-order(mydata[,8]) sorted.mydata<-mydata[rank.by.Y1,] after that, I replaced Y1's values with values ranging from 1

I've been playing around with various table tools, trying to construct a fairly simple cross-tab. It shouldn't be hard, but for some reason it turning out to be (for me). If I want to see how many men and how many women agree with a agree/disagree question (coded 1,0), I can do this: >attach(mydata) >mytable <- table(male, q1.bin) # gender and a binary response variable

I have a sparse contingency table (most cells are 0): > xtabs(~.,data[,idx:(idx+4)]) , , x3 = 1, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 31 2 0 0 112 3 0 0 94 , , x3 = 2, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 3, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 1, x4

Dear Users, I'm a complete novice to R. I need to do a crosstabs in R, but my data is almost completely alphanumeric (with some variables scaled). The Table routine does not seem to accept alphanumeric data. What should I do? Do I need to recode it? How should I do that? Thanks in advance, Wilfred

Dear List: Most of the analysis I do involves contingency tables. I am migrating to R from Stata and I have a number of questions about using contingency tables in R. I suspect that most of the things I want to do are very short R scripts that people on this list probably have. I wonder if you would be willing to share them. First, the presentation of tables by table() is not

How does one ideally handle and display multidimenstional contingency tables in R v. 2.6.2? E.g.: > prob1<- data.frame(victim=c(rep('white',4),rep('black',4)), + perp=c(rep('white',2),rep('black',2),rep('white',2),rep('black',2)), + death=rep(c('yes','no'),4), count=c(19,132,11,52,0,9,6,97)) > prob1 victim perp