similar to: Plot with a factor variable which has large values

Dear All, Writing sooner than I thought I'd need to. I'm using R 2.4 on Mac OS X, with RODBC, PostgreSQL 8.1 and Actual's ODBC driver. I have all my data in Filemaker 8.5, but it is automatically exported into PostgreSQL for analysis as Filemaker's ODBC and JDBC access is awful, slow and has a tendency to crash. I have disability data where for each patient there is a survival

I have a dataframe that looks like this: > str(chr) 'data.frame': 84 obs. of 7 variables: $ county: Factor w/ 3 levels "Broome","Nassau",..: 3 3 3 3 3 3 3 3 3 3 ... $ item : Factor w/ 28 levels "Access to healthy foods",..: 21 19 20 18 16 3 2 6 17 8 ... $ value : num 8644 15 3.5 3.9 7.7 ... $ low : num 7897 9 2.5 2.6 7 ... $ high : num 9390

Dear R-Helpers, Apologies in advance as this is partly (widely ?) OT. Not sure where to ask, R is my favorite computer tool (no kidding) and there are plenty of knowledgable and helpful people on the list. Background: There are discussions among experts and regulatory authorities (cf guideline http://www.emea.europa.eu/pdfs/human/ewp/056598en.pdf) that, in for example Amyotrophic Lateral

I have 2 positions open with a top pharmaceutical company in New Jersey. This position is not requiring pharmaceutical experience as long as the candidate has strong SAS and R experience. In particular they are looking for strong graphics experience in S-Plus/R (lattice or Trellis?TM graphics). If you would like to learn more about this position please contact Christina Kinchen at ckinchen at

I have an opening for a Senior Programmer in Central New Jersey with a large Pharmaceutical company. Senior Programmer needed to create applications for automating statistical analyses and creating reports. The candidate will generate user requirements, develop and write code, and take the lead in the validating the applications. The primary emphasis will be on creating applications to automate

I currently have an opening with a large Pharmaceutical company in New Jersey. If you have any interest please contact Christina Kinchen at 800-684-9921 ext 220 or 407-548-0670 email: Ckinchen at smithhanley.com. We also have a great referral program if you know of anyone who is a fit. Please feel free to contact me with any questions. Job Details: --3+ years' bioinformatics research

We are trying to read a sas export file into R. (Works fine on Mac by ftping the export file from solaris box and then importing to R with read.xport, this gives rational numbers etc.) Trying to do this on an IBM Power p655 running linux, reading the same sas export file as used on MAC, in this case the results are not rational. Many of the numbers are interpreted as INF etc. Is it possible

Good Morning, Is it possible to use the R program for a CFA with dichotomous data? Thank you, Kathleen Kathleen Kemp, M.A. Doctoral Clinical Psychology Student, Concentration: Forensic Psychology Drexel University Philadelphia, PA 19104 kk354@drexel.edu [[alternative HTML version deleted]]

http://www.tmcnet.com/tmcnet/articles/2004/031704rt.htm Previous article by same author: http://www.tmcnet.com/it/0104/0104PO.htm

i have recently rebuilt dovecot on my mail server as i wanted to add SSL support for it. well, my OpenSSL libs are 64-bit, so what they hey, i'll build dovecot 64-bit as well. worked just fine, no issues at all. the setup is: Solaris 9/SPARC Sun C compiler Dovecot 0.99.14 after rebuilding it 64-bit, i now have a small problem however. I cannot save messages to IMAP folders from Mail.app

I'm trying to make a factor with levels for day of week, appear as Monday-Sunday, rather than alphabetically. I'm using reorder.factor from gdata package, but obviously not using it properly. What am I doing wrong? Thanks. >data <- read.table("DataEarly2008.txt", sep=" ", header=T, as.is=1:2) >str(data) 'data.frame': 7953 obs. of 9 variables: $

Hi I would really appreciate some help with my code for coxme... My data set I'm interested in survival of animals after an experiment with 4 treatments, which was performed on males and females. I also have two random factors: Response variable: survival (death) Factor 1: treatment (4 levels) Factor 2: sex (male / female) Random effects 1: person nested within day (2 people did

Dear R graphics gurus, Another question about lattice graphics. This time I would like to plot means and confidence intervals by group factor in a lattice graph. I can not find any working lattice examples. Maybe a custom panel function is the answer, but that is a bit beyond me for now. The individual plots within the lattice graph could look like this: # Example with confidence intervals

Are there any suitable routines that perform factor analysis of categorical or mixed categorical/continuous data in R? Stuart Dr Stuart Leask MA MB BChir (Cantab) MRCPsych Clinical Lecturer in Psychiatry, University of Nottingham Dept Psychiatry Duncan Macmillan House, Porchester Road, Nottingham. NG3 6AA. UK tel. 00 44 115 969 1300 xtn 40784 fax 0115 955 5352

Hi all. This is perhaps more a statistics question but I'm hoping someone can help me. I have a group of patients for whom I'm looking at beat to beat RR interval changes. I have plotted the difference between one beat length and the next against the difference between the previous beat length and the current one. This gives me a plot with four quadrants: the bottom left corresponding to

I know this issue has been beat to death on the newsgroups, but I have not yet found an answer. I will make an attempt to include all the necessary info. Description of Problem: I am having problems trying to access large files (>2GB) on mounted smbfs volumes. To clarify, I am attempting to view large files that exist on an NT server, from my Linux box, and getting erroneous results.

Brian Ripley pointed out that there is already an R function scale() that does the work of my standardize(). -Greg -----Original Message----- From: Warnes, Gregory R Sent: Friday, January 18, 2002 9:38 AM To: 'Stuart Leask' Cc: 'r-help at stat.math.ethz.ch' Subject: RE: z-scores for different factor levels Hi Stuart, I often use this small function standardize <-

Dear UseRs, Suppose I have data regarding smoking habits of a prospective cohort and wish to determine the risk ratio of colorectal cancer in the smokers compared to the non-smokers. What do I do at the end of the study with people who die of heart disease? Can I just censor them exactly the same as people who become uncontactable or who die in a plane crash? If not, why not? I'm thinking

There seems to be a new regression in current llvm/compiler-rt 3.2 branch. On 86_64-apple-darwin12, I am seeing the failure... [100%] Running all regression tests lit.py: lit.common.cfg:19: note: using clang: '/sw/src/fink.build/llvm32-3.2-0/llvm-3.2/build/bin/clang' lit.py: lit.cfg:171: note: using clang: '/sw/src/fink.build/llvm32-3.2-0/llvm-3.2/build/bin/./clang' FAIL:

Interesting figures. Some corresponding figures for flac 1.0 for a set of 404 CDs, with a total of 4357 tracks are: Opt Uncompressed Compressed Ratio Encode Time --- ------------ ----------- ------ ----------- -8 234507744748 127468328349 0.5436 n/a Admittedly, this set includes at least one country album, and has a fair share of jazz in it. The worst-case track in this set