similar to: Predicted Cox survival curves - factor coding problems..

I am trying to use the survfit() function with the newdata argument to produce predicted survivor curves for a particular covariate profile. The main purpose of the plot will be to visualise the effect of snp1, coded 0 and 1. In my Cox model I have stratified by one variable, edu, and so I know I will automatically get a separate curve for each strata. My problem is how to deal with the

Hello I have two data frames, SNP4 and SNP1: > head(SNP4) Animal Marker Y 3213 194073197 P1001 0.021088 1295 194073197 P1002 0.021088 915 194073197 P1004 0.021088 2833 194073197 P1005 0.021088 1487 194073197 P1006 0.021088 1885 194073197 P1007 0.021088 > head(SNP1) Animal Marker x 3213 194073197 P1001 2 1295 194073197 P1002 1 915 194073197

Hello, I'm running a few tests here with two locations. site1: server-site1.gsg.local subnet 192.168.200.0/24 site2: server-site2.gsg.local subnet 192.168.190.0/24 both are connected via VPN. I migrated an samba3 domain at server-site1 it gets Default-First-Site-Name assigned. Then I joined the new samba4 domain withe server-site2. Both servers work and i can join and access them with

Why does the assignment of a 3178x93 object to another 3178x93 object remove the dimension attribute? > GT <- array(dim = c(6,nrow(InData),ncol(InSNPs))) > dim(GT) [1] 6 3178 93 > SNP1 <- InSNPs[InData[,"C1"],] > dim(SNP1) [1] 3178 93 > SNP2 <- InSNPs[InData[,"C2"],] > dim(SNP2) [1] 3178 93 > dim(pmin(SNP1,SNP2)) [1] 3178 93

g''day all, I need help with this please. I have a dataset of site names and years they were trapped in (a subset of it is bs, below) and a dataset of sites that actually caught animals (subsetted as brep, below). I need to add to brep, a row with a zero in the classcount column, for every year each site was trapped but caught nothing. so for Site 1, I need to add rows that say

I am trying to use the function gl (generate levels), and would like to make levels with different number of replications. Does anyone know how to generate different number of replications in each level? Something like: [1] Site1 Site1 Site1 Site1 Site1 Site1 Site1 [8] Site2 Site2 Site2 Site2 Site2 Thanks in advance -- Rog?rio R. Silva MZUSP http://www.mz.usp.br Linux/Debian User # 354364

Dear R-experts, I have a table with following collumns: State, SamplePlot, Species and BodySize. I sampled bird species at 34 SamplePlots and 5 States (regions) monthly during two years. On each bird record I measured bodysize and identified the species. So I have many records of each species (about 150 species) at each SamplePlot and each Region (State). Now I would like bootstrap

hii guys i have some issue with dns in samba 4 i have install and setup 2 samba dc in different Site site2 dc joint to site1 dc, with internal dns topology : site1 --- openvpn server --- firewall --- wan --- openvpn client --- site2 192.168.1.0/24 192.168.2.0/24 in site1 i have some application let say email server: mail.local.lan > 192.168.1.2 web server : web.local.lan > 192.168.1.3

Hello, I'd like to transpose data to create an analysis-friendly dataframe. See below for an example, I was unable to use t(x) and I couldn't find a function with options like PROC TRANSPOSE in SAS. The ideal solution handles variable quantities of SITE - but beggars can't be choosers. :-) Thank you in advance, Mike ## INPUT DATA USER_ID<-c(1,1,1,2,2,2,3,3,4) SITE

Dear R helpers I have a table and i need to make new table table1: sire snp1 snp2 snp3 snp4 snp5 snp6 snp7 snp8 snp9 snp10 snp11 snp12 snp13 snp14 snp15 8877 -1 -1 -1 -1 0 0 -1 -1 -1 0 1 1 1 -1 -1 7765 1 1 1 0 0 0 -1 1 1 1 0 0 0 1 0 8766 1 1 -1 0 -1 -1 0 -1 0 -1 -1 -1 0 1 0 6756 0 1 0 -1 1 -1 -1 0 0 0 0 -1 0 1 1 5644 -1 0 1 -1 0 0 0 0 -1 -1 0 0 0 0 1 I have table2 sire

I am attempting to join several dataframes that summarize sampling effort for different samples into one large data.frame/table. I have looked at the merge command, but have not been clever enough to figure out how to get it to do what I want. A simplified example of what I am trying to do: The dataframes I have look like this (they were generated using the table command) species1.effort

Dear all, I am trying to extract rows from a data.frame based on the rowSums != 0. I want to preserve rownames in the first column in the subset. Does anyone know how to extract all species that don't have rowSums equal to zero? Here it is: # dataset x <- data.frame( species=c("sp.1","sp.2","sp.3","sp.4"), site1=c(2,3,0,0), site2=c(0,0,0,0),

Hi, I've got a quite tricky question. I have a txt file, named 'temp.txt', as the following: snp1 snp2 snp3 AA 00 00 GG GG 00 00 AA 00 I want to read the file into R. 1) when I use 'read.table' without 'header=T' option, > temp <- read.table('temp.txt') # I got > temp V1

Hi, I have a large dataset on which I would like to do the following: x<-data.frame(id=c(1,2,3), snp1=c("AA","GG", "AG"),snp2=c("GG","AG","GG"),snp3=c("GG","AG","AA")) > x id snp1 snp2 snp3 1 1 AA GG GG 2 2 GG AG AG 3 3 AG GG AA And then

Hello all, I hope some of you can come to my rescue, yet again. I have two genetic datasets, and I want one of the datasets to have only the columns that are in common with the other dataset. Here is a toy example (my real datasets have hundreds of columns): Dataset 1: Individual SNP1 SNP2 SNP3 SNP4 SNP5 1 A G T C A 2 T C A G T 3 A C T

Hi ihave one table that look like SNP1 SNP2 SNP3 SNP4 SNP5 SIRE1 1 -1 -1 1 -1 SIRE2 1 -1 1 1 1 SIRE3 -1 -1 1 1 0 SIRE4 -1 1 1 0 1 SIRE5 -1 1 -1 -1 1 SIRE6 0 0 0 1 -1 SIRE7 -1 0 -1 1 1 SIRE8 1 -1 NA 0 NA SIRE9 -1 1 1 -1 -1 SIRE10 1 1 1 1 1 table 2 only one line SNP1 SNP2 SNP3 SNP4 SNP5 SIRE100 -1 -1 1

Dear all, how can I, with R, transform a presence-absence (0/1) matrix of species occurrences into a presence-only table (3 columns) with the names of the species (1st column), the lat information of the sites (2nd column) and the lon information of the sites (3rd column), as given in the below example? Thanks a lot for your help! Christian my dataframe: site lat lon spec1 spec2 spec3 spec4

Hello all, here's a real-world example: I'm measuring a quantity (d) at five sites (site1 thru site5) on a silicon wafer. There is a clear site-dependence of the measured value. To find out if this is a measurement artifact I measured the wafer four times: twice in the normal position (posN), and twice rotated by 180 degrees (posR). My data looks like this (full, self-contained code at

Hello, How can I randomly sample individuals within a sites from a site (row) X species abundance (column) data frame or matrix? As an example, the matrix "abund2" made below. ##### (sorry, Im a newbie and this is the only way I know to get an example on here) abund1 <- c(150, 300, 0, 360, 150, 300, 0, 240, 150, 0, 60, 0, 150, 0, 540, 0, 0, 300, 0, 240, 300, 300,

Hello R list, I have a list of data frames, in the form (dump output for an example list follows message): $site1 year data 1 2000 0.03685042 2 2001 0.02583885 6 2005 0.02480015 7 2006 0.03458745 $site2 year data 1 2002 4.071134e-03 2 2003 -4.513524e-08 3 2004 8.336272e-08 4 2005 2.270803e-08 5 2006 1.263597e-02 6 2007 NaN I would like to plot each