similar to: bugs or imperfect implementation?

I have been tinkering with mosaicplot() and friends as a way of learning R. As part of this, I've written a pair.table() method for mosaic matrices, and would like to extend mosaicplot to work with loglin and logln (MASS) objects. I'm using R 1.4.0 on Win 98. I've been trying to figure out the formula interface, and think there's a bug, but not sure how to find it, yet alone fix

Dear R-helpers, Suppose I have dataset like this below: data(HairEyeColor) dfHEC <- as.data.frame(as.table(HairEyeColor)) my.dfHEC <- data.frame(Hair=rep(dfHEC$Hair,dfHEC$Freq), Eye=rep(dfHEC$Eye,dfHEC$Freq), Sex=rep(dfHEC$Sex,dfHEC$Freq)) my.dfHEC my.dfHEC$Hair my.dfHEC$Eye my.dfHEC$Sex and I know all levels for Hair, Eye and Sex. In my case, I

I'm looking for a way to generalize the calculation of (log) odds ratios for 2 x 2 x {strata} frequency tables in vcd::oddsratio() to R x C x {strata} tables. For an R x C table, F, odds ratios can be defined in several ways; one simple way, particularly for tables with ordered factors, is to calculate the set of continuation odds ratios, based on the (R-1)x(C-1) set of 2x2 tables with

My question is based on an example provided in the following: Referencing: Statistics with R Vincent Zoonekynd <zoonek at math.jussieu.fr> 6th January 2007 URL: http://zoonek2.free.fr/UNIX/48_R/all.html data(HairEyeColor) a <- as.table( apply(HairEyeColor, c(1,2), sum) ) # Provided Example barplot(a, beside = TRUE, legend.text = attr(a, "dimnames")$Hair) # I

Hello, I am trying to use the extended assocplot() function: assoc(), from vcd package. Trouble is that it cannot even run its own examples on my installation. I get this output: $> example(assoc) assoc> data("HairEyeColor") assoc> (x <- margin.table(HairEyeColor, c(1, 2))) Eye Hair Brown Blue Hazel Green Black 68 20 15 5 Brown 119 84 54

The data is in the attachment. What I wanna get is: , , Sex = Male Eye Hair Brown Blue Hazel Green Black 32 11 10 3 Brown 53 50 25 15 Red 10 10 7 7 Blond 3 30 5 8 , , Sex = Female Eye Hair Brown Blue Hazel Green Black 36 9 5 2 Brown 66 34 29 14 Red 16 7 7 7 Blond 4

I've just started learning R, so I'm still on the steep part of the learning curve, but my enthusiasm was heightened by learning that there's a very nice implementation of mosaicplot(). As a learning project, I've already done a basic implementation of a pairs.table() function which does a mosaic scatterplot matrix, and now I'm trying to do conditional mosaic plots (discrete

Dear all, I noticed the following while playing around with fitting log-linear models to contingency tables using R 1.8.1, but the problem also exists under R 1.9.0. A reproducible example uses the following contingency table: > library(MASS) > data(quine) > tmp <- with(quine, expand.grid(Eth=levels(Eth), Sex=levels(Sex), + Lrn=levels(Lrn), Age=levels(Age)))

I have an application where I have a function to calculate results for a 2-way table or matrix, which returns a matrix with one less row and column. To keep this short, the function below captures the structure: fun2way <- function(f){ if (!length(dim(f)) ==2) stop("only for 2-way arrays") R <- dim(f)[1] C <- dim(f)[2] f[1:(R-1), 1:(C-1)] } Now, I want to

Dear everybody: We used the fine foreign library to bring in an SPSS dataset that was about 9 megabytes and I can squeeze it into a much smaller R object using compression with save(ndat, file="NatAnnES2000.rda", compress=T). I can use load() to get the "ndat" dataframe back, that's all good as far as I can see. If I put that file in the data subdirectory, then the

Reading "R Internals" made me believe that R_UnboundValue was a placeholder that would be skipped over in variable lookup. viz. the section of R Internals "Hash tables" says "items are not actually deleted but have their value set to R_UnboundValue.", which seems to align with what I read in envir.c. So, I reasoned, if I have a function that returns R_UnboundValue,

It appears that HSAURtable only works on two dimensional tables. Is this correct? For example, here is HairEyeColor: , , Sex = Male Eye Hair Brown Blue Hazel Green Black 32 11 10 3 Brown 38 50 25 15 Red 10 10 7 7 Blond 3 30 5 8 , , Sex = Female Eye Hair Brown Blue Hazel Green Black 36 9 5 2

Hi, I'm trying to build a hierarchical logistic regression model with lme4 package, but I have a problem on selecting the variables to include in this model. In a simple logistic regression, using Forward selection, i use a likelihood ratio test to check which variables i should include in the model, using the function add1(). The problem is that this function doesn't work with the

I'm trying to find a way to change the font size in a mosaic plot (the grid version, not the base graphics one). Here's an example to demonstrate: #Basic plot library(vcd) mosaic(HairEyeColor, shade = TRUE) #Bad first guess: this stops the default cell colouring, and doesn't change the font size mosaic(HairEyeColor, shade = TRUE, gp=gpar(fontsize=16)) #This successfully changes

Full_Name: Reginaldo Constantino Version: 2.8.0 OS: Ubuntu Hardy (32 bit, kernel 2.6.24) Submission from: (NULL) (189.61.88.2) For many tables, chisq.test with simulate.p.value=TRUE gives a p value that is obviously incorrect and inversely proportional to the number of replicates: > data(HairEyeColor) > x <- margin.table(HairEyeColor, c(1, 2)) >

Exec. Summary: step() basically ``fails'' whereas MASS' stepAIC() does work This may not be a bug in the strictest sense, but at least something for the wish list. Unfortunately I have no time currently to investigate further myself but want to be sure this won't be forgotten: The example is using a real data set with 216 observations on 9 variables -- where we have

Hi, I would like to do a multiple correspondence analysis with the mca function in the MASS library on data that I have as a contingency table (which I've tried converting to a data frame). For example, ========= > data(HairEyeColor) > hair.df <- as.data.frame(HairEyeColor) > hair.df Hair Eye Sex Freq 1 Black Brown Male 32 2 Brown Brown Male 38 3 Red

Two proposals for mosaicplot(): - The argument "sub" should not be ignored. Example: mosaicplot( HairEyeColor, sub = 'test of sub' ) - To be able to discern also longer axis labels the argument "las" or par(las=2) should not be ignored. Example: mosaicplot( HairEyeColor, las=2 ) Thanks Wolfram

This is a follow-up to a query that was posted regarding some problems that emerge when running anova analyses for cox models, posted by Mathias Gondan: Matthias Gondan wrote: >* Dear List,*>**>* I have tried a stratified Cox Regression, it is working fine, except for*>* the "Anova"-Tests:*>**>* Here the commands (should work out of the box):*>**>*

the data is : >table.8.3<-data.frame(expand.grid( marijuana=factor(c("Yes","No"),levels=c("No","Yes")), cigarette=factor(c("Yes","No"),levels=c("No","Yes")), alcohol=factor(c("Yes","No"),levels=c("No","Yes"))), count=c(911,538,44,456,3,43,2,279))