similar to: rbind.data.frame drops attributes for factor variables

Hello, I'm attempting to use the ratetable argument to survexp in the survival package. I use the example from the ?survexp help page below, and then slightly modify it to produce an error. library(survival) data(pbc) #fit a model without any factors pfit1 <- coxph(Surv(time, status > 0) ~ trt + log(bili) + log(protime) + age + platelet, data=pbc) #this works as expected

Hi all, When I use rbind() or rbind.data.frame() to add a row to an existing dataframe, it appears that attributes for the column of type "factor" are dropped. I see the following post with same problem. However i did not see any reply to the following posting offering a solution. Could someone please help.

When I use rbind() or rbind.data.frame() to add a row to an existing dataframe, it appears that attributes for the column of type "factor" are dropped. See the sample example below to reproduce the problem. Please suggest How I can fix this. Thanks, Sammy a=c("Male", "Male", "Female", "Male") b=c(1,2,3,4) c=c("great", "bad",

Hello - I am wanting to create some Cox PH models with coxph (in package survival) using different datasets. The code below illustrates my current approach and problem with completing this. ### BEGIN R SAMPLE CODE ############################## library(survival) #Define a function to make test data makeTestDF <- function(n) { times <- sample(1:200, n, replace = TRUE) event

Dear R-help - Thanks to those who replied yesterday (Christos H. and Thomas L.) regarding my question on coxph and model formula, the answers worked perfectly. My new question involves the following. I want to run several coxph models (package survival) with the same dataset, but different subsets of that dataset. I have found a way to do this, described below in functions subwrap1 and

Hi R users: When I try to merge or bind (cbind or rbind) two series, both with a "FinCenter" different that GMT, the result is "GMT" not the original financial center? What am I doing wrong? ###################################################### require(timeSeries) getRmetricsOptions("myFinCenter") setRmetricsOptions(myFinCenter = "America/Bogota")

Hi all, after using Amelia II to create 10 imputed data sets I need to average them to have one unique data that includes the average for each cell of the variables imputed, in addition to the values for the variables not imputed. Such data has many variables (some numeric, other factors), and more than 20000 observations. I do not know how to average them out. Any help? Below I provide a small

Dear, I have a dataset with 4 subjects (see ID in example), and 4 treatment (see TRT in example) which are tested on 2 locations and in 3 blocs. By using Lattice dotplot, I made a graph that shows the raw data per location and per bloc. In that graph, I would like to have a reference line per bloc that refers to the first treatment (T1). However, I can not find how to do that. I can make

Dear R-help - I have thought about this question for a bit, and come up with no satisfactory answer. Say I have the numeric vector t1, given as t1 <- c(1.0, 1.5, 2.0, 2.5, 3.0) I simply want to reliably extract the unique integers from t1, i.e., the vector c(1, 2, 3). This is of course superficially simple to carry out. However, my question is related to R FAQ 7.31, "Why

I would like to have a lattice conditioning ( | var ) variable have expression() as values because I want panel labels to be able to use plotmath notation for subscripts, etc. lattice barks at this. Does anyone know of a trick workaround? An attempted example program is below. Thanks -Frank require(lattice) set.seed(1) var <- c(rep('A', 100), rep('B', 100)) trt <-

Hi, I have 16 tables of 39 variables with around 1500 to 3500 cases in each table. These 16 tables are in 16 different data frames. I want to merge them in a single large data frame, so: All <- rbind(T1, T2, ...) The problem: it is VERY slow, and takes a lot of memory (> 500 Mb) on my Athlon XP1800+, 1.75 Go memory, Win 2000 Pro SP1, R 1.4.1. Any suggestion to improve speed, and/or memory

Hi all, I bumped into this awkward zoo behaviour. I'd be half tempted to call it a bug, what do you think? It's annoying to work around it :( I wonder if this was the behaviour of older zoo versions, I can't remember coming across this sort of thing... > version _ platform i386-pc-solaris2.10 arch i386 os solaris2.10 system i386,

On 18/02/2019 4:08 p.m., Matt Dowle wrote: > Dear all, > > I'm experiencing an unusual installation error for one package. Could > anyone suggest how I can best investigate this from here please? I'm sorry > this isn't very much to go on. Hopefully someone can point me in the right > direction. When packages are installed, a hidden environment is created called

Hi , I have a data set with recurrence time (up to four) of myocardial infarction (MI). Part of the file is showing below: Num1 Trt Sex Time T1 T2 T3 T4 1011 1 1 9 1211 0 1 59 3020 1 2 14 3 1245 0 1 18 12 16 3069 1 2 26 6 12 13 2051 0 1 53 3 15 46 51 The data consist of the following eight variables: Num1 , patient number Trt, treatment group (1=placebo and 2=drug) Sex,

Full_Name: Hin-Tak Leung Version: R 2.2.1 OS: x86_64-redhat-linux-gnu Submission from: (NULL) (131.111.186.92) rbind/cbind is unimplemented for raw (RAWSXP) types. I have a working patch implementing the functionality, to follow. --please do not edit the information below-- Version: platform = x86_64-redhat-linux-gnu arch = x86_64 os = linux-gnu system = x86_64, linux-gnu status = major

Full_Name: Lutz Prechelt Version: 2.4.1 OS: Windows XP Submission from: (NULL) (160.45.111.67) I stack a number of data.frames using rbind. Each of these dataframes has a column 'authorname', which is a factor and a column author = unclass(authorname) as piecewise pseudonyms. When using rbind to stack these dataframes, R warns about invalid factor levels and inserts all NAs in the author

Hi, FYI, I just notice that on Windows (but not Linux) it is orders of magnitude (below it's 50x) faster to serialize() and object to a temporary file and then read it back, than to serialize to an object directly. This has for instance impact on how fast digest::digest() can provide a checksum. Example: x <- 1:1e7; t1 <- system.time(raw1 <- serialize(x, connection=NULL));

Dear R users, I have a data frame in the form below, on which I would like to make normality tests on the values in the ExpressionLevel column. > head(df) ID Plant Tissue Gene ExpressionLevel 1 1 p1 t1 g1 366.53 2 2 p1 t1 g2 0.57 3 3 p1 t1 g3 11.81 4 4 p1 t2 g1 498.43 5 5 p1 t2 g2 2.14 6 6 p1 t2 g3 7.85 I

Dear All, on rbind:ing together a number of data.frames, I found that character variables are converted into factors. Since this occurred for a data identifier, it was a little inconvenient and, to me, unexpected. (The help page explains the general procedure used. I also found that on forming a data frame, character variables are converted to factors. The help page on read.table has the

Dear all, I'm experiencing an unusual installation error for one package. Could anyone suggest how I can best investigate this from here please? I'm sorry this isn't very much to go on. Hopefully someone can point me in the right direction. The problem seems to be my library. It is large (3,418 packages) and I'd like to avoid rebuilding it, if possible. All packages are up to