search for: logratios

Hello. A quick question about incorporating variation due to study in the metafor package. I'm working with a particular data set for meta-analysis where some studies have multiple measurements. Others do not. So, let's say the effect I'm looking at is response to two different kinds of drug treatment - let's call their effect sizes T1 and T2. Some studies have multiple

I am using R to do a loess normalisation procedure. In 1.5.1 I used the following commands to normalise the variable "logratio", over a 2d surface (defined by coordinates x and y): > array <- read.table("121203B_QCnew.txt", header=T, sep="\t") > array$logs555<-log(array$s555)/log(2) > array$logs647<-log(array$s647)/log(2) >

I have got following error in drawing wavelet fitting. can some one help? > library(faraway) > data(lidar) > newlidar<-lidar[c(1:128),] > library(wavethresh) > wds <- wd(newlidar$logratio) > draw(wds) Error in plot.default(x = x, y = zwr, main = main, sub = sub, xlab = xlab, : formal argument "type" matched by multiple actual arguments [[alternative HTML

Dear R-users, I have an outcome variable and I'm unsure about how to treat it. Any advice? I have spending data for each county in the state of California (N=58). Each county has been allocated money to spend on any one of the following four categories: A, B, C, and D. Each county may spend the money in any way they see fit. This also means that the county need not spend all the money that

Hi list I am just beginning to understand the complexities of linear mixed effects models. Maybe someone can give advise concerning the following problem: I have two groups of surgical patients in which repeated laboratory measurements were taken over time after surgery. I decided that lme would be the best model to fit the data. I already fitted the model lme(logratio ~ gr*I(pod-10) +

HI everyone, I''m trying to assign colors to multiple lines in a graph. Problem is I don''t want to type in as many colors as there are lines....is there a way around this? In brief, I''m plotting the logratio for up to 60 samples and want a different color for each sample. Here is the code I''m using now.. Any help is greatly appreciated.. Best LT data <-

...ot class directly? Here is an example explaing my question. Everything relates to S3/UseMethod classes and methods. I have an object x of class MicroarrayMatrix, which inherits from class Matrix. The "core" object of x is a simple matrix. In other words, I basically have x <- matrix(logratios, ncol=nbrOfSpots, nrow=nbrOfSlides) class(x) <- c("MicroarrayMatrix", "Matrix") Both these classes implement their own version of the "["() method. The "["() method of MicroarrayMatrix will return (spot, slide) values if called with two indices. Example...

I am attempting to created colClasses for several tables, then read only specific columns. There are two different table layouts that I am working with. If I use exclusively one layout, the script works perfectly, but if I mix the layouts, it fails to grab the correct columns form layout that is read in second. It appears that colClasses fails to adopt the new structure after the first iteration.

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Hi, I am new to R. I am trying to figure out how to graph expression data from the TCGA database. If I understand correctly the expression data I have downloaded is from a microarray using the AgilentG4502A. I've had trouble reading into R in the level I, level II, and the gene expression analysis data using >dat<-read.table("C:\\file.txt", header=T, row.names=1) for

Dear R-Help members, I am using Simon Wood`s mgcv package version1.7-22and R version 3.0.0 (2013-04-03) for fitting a GAM-Model to the LIDAR Data contained in the "SemiPar" package. Here is the code for fitting the model and for plotting the result: data("lidar") attach(lidar) ### # mgcv fitting ### gam_fit <- gam(logratio ~ s(range, k = 40, bs = "cr"), gamma