similar to: problems with printing and plotting aareg

Hi all, I've ventured into the world of nonparametric survival and I would like to use the "maxtime" option for printing and plotting my aareg fit. However, my fit does not have "test.var2" and this stops the print and plot when adding a maxtime. My code is as follows: Response<-Surv(Time,Event) Model<-aareg(Response~Factor1*Factor2)

On 06/05/2013 12:33 AM, r-help-request at r-project.org wrote: > Dear friends - I'm on windows 7, R 2.15.2 > > when I run the example for aareg in survival package I see this: > > plot(lfit[4], ylim=c(-4,4)) > error in xy.coords(x, y, xlabel, ylabel, log) : > 'x' is a list, but does not have components 'x' and 'y' > > Is that a matter

Is names(model1$coef) what you're looking for? -----Original Message----- From: Kenneth Cabrera [mailto:krcabrer at epm.net.co] Sent: 29 November 2002 10:36 Cc: R-help at stat.math.ethz.ch Subject: [R] Obtaining the variable names of a glm object Hi, R users! Suppose I make a model like this:

I have a table (output from table(factor1,factor2)). I would like to use write.table to output that table to a file. However, it seems that as.data.frame converts such a table to three columns, Var1, Var2, and Freq rather than converting to the data.frame with equivalent numbers of rows and columns. I can use write.matrix from the MASS package, but then I get no rownames. Any hints here?

I'd like to get a long data set of minimum values from groups in another data set. The following almost does what I want. (Note, I'm using the word factor differently from it's meaning in R; bad choice of words) myframe = data.frame(factor1 = rep(1:2,each=8), factor2 = rep(c("a","b"),each=4, times=2), factor3 = rep(c("x","y"),each=2, times=4),

Hello everyone, I am just a tyro in R and would like your kindly help for some problems which I've been struggling for a while but still in vain. I have a time-series file (with some missing value ) which looks like time[sec] , Factor1 , Factor2 00:00:00 01.01.2007 , 0.0000 , 0.176083 01:00:00 01.01.2007 , 0.0000 , 0.176417 [ ... ] 11:00:00 10.06.2007 , 0.0000 , 0.148250 12:00:00 10.06.2007

Hello! I am aggregating using a formula in aggregate - of the type: aggregate(cbind(var1,var2,var3)~factor1+factor2,sum,data=mydata) However, I actually have an object (vector of my variables to be aggregated): myvars<-c("var1","var2","var3") I'd like my aggregate formula (its "cbind" part) to be able to use my "myvars" object. Is it

Dear R people, I have a couple of questions about post-doc analyses for 2 by 2 within subjects ANOVA. I conducted a psycholinguistic study that combined a 2 by 2 design and a latin square design. Specifically, I had 32 items each of which generated 4 conditions. Participants saw each of the 32 items only once: 8 in Condition A, 8 in B, 8 in C, and 8 in D. The table below serves as an example.

Dear all, I use a nested design with lm and glm, with factor2 nested within factor1. In order to test for the significance of both factors, I use anova tables on the obtained models such as follows: /> mod1<-lm(A~factor1/factor2) > amod1<-anova(mod1, test="F") Analysis of Variance Table Response: A Df Sum Sq Mean Sq F value Pr(>F) factor1

Dear R users, I posted a couple of questions and got no response, so I am giving it another shot. I ran an experiment with a TWO-WAY within subject design. A sample dataset is in http://www-scf.usc.edu/~hex/data.txt I already ran ANOVA by using the following formula: aov(RT~Factor1*Factor2 + Error(Subject/(Factor1*Factor2)), data=data) and I obtained the following information: -------------

Hello there, I have a situation where I would like to select the first row of a particular factor for a data frame (data example below). So that is, I would like to select the first entry when the factor1 =A and then the first row when factor1=B etc. I have thousands of entries so I need some general way of doing this. I have a minimal example that should illustrate what I am trying to do. I am

Full_Name: Tanya Logvinenko Version: 1.7.0 OS: Windows 2000 Submission from: (NULL) (132.183.156.125) For unbalanced design, I ran into problem with ANOVA (aov function). The sum of squares for only for the second factor and total are computed correctly, but sum of squares for the first factor is computed incorreclty. Changing order of factors in the formula changes the ANOVA table. For the

Hi All, I have a 4-dimensional data. I'm using barchart() function from lattice package. The R code and data are below - code includes one for stack=TRUE and other for stack=FALSE. I would like to present the data in another form which would be plotting Factor3 levels (P, Q, R, S) as two stacked bars (side by side). Like, for each level of Factor1 there should be two bars: first bar showing

I am attempting to replicate some of my experience from SAS in R and assume there are best methods for using a combination of summary(), subset, and which() to produce a subset of mean values by categorical or ordinal factors. within sas I would write proc means mean data=dataset; class factor1 factor2 var variable1 variable2; RUN; producing an output with means for each variable by factor

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

Hi everyone (again), before you all start screaming that the reordering of factors has been discusse on several threads and is not particular to ggplot2, hear me out. I can easily reorder my x-axis factor in facet.grid() in ggplot2. What I cannot reorder are the factors represented on the strips. I can see that the graphs are changing, so I am afraid of what it is I am doing. Why is ggplot2

Hi All, I have googled and tried finding if someone has ever tried producing (Grouped + Stacked) Barplot. I couldn't find one. My data needs to be reshaped, but once it is done it would be something like this: Factor1 Factor2 Factor3 Value A X P 10 A X Q 20 A Y P 20 A Y Q 5 A Z P 20 A Z Q 10 B X P 20 B X Q 10 B

Dear Users, I ran factor analysis using R and SAS. However, I had different outputs from R and SAS. Why they provide different outputs? Especially, the factor loadings are different. I did real dataset(n=264), however, I had an extremely different from R and SAS. Why this things happened? Which software is correct on? Thanks in advance, - TY #R code with example data # A little

Dear list, I have a question regarding the meaning of intercept term in a two-way anova model without interaction term. for example (let's assume there is no interaction between factor1 and factor2) : > df         val        factor1 factor2 1  48.61533       A      t1 2 171.13535       B      t1 3  65.96884       C      t1 4  63.71222       A      t2 5  80.22049       B      t2 6 

I can think of many brute-force ways to do this outside of R, but was wondering if there was a simple/elegant solution within R instead. I have a table that looks something like the following: Factor1 Factor2 Value A 11/11/2009 5 A 11/12/2009 4 B 11/11/2009 7 B 11/13/2009 8 >From that I need to generate all permutations of Factor1 and Factor2 and force a 0 for any combination that doesn?t