similar to: variable syntax problem

Displaying 20 results from an estimated 300 matches similar to: "variable syntax problem"

2004 Jul 21
2
RE: Comparison of correlation coefficients - Details
Dear all I apologize for cross-posting, but first it is accepted custom to thank the repliers and give a summary, and second I have still the feeling that this problem might be a general statistical problem and not necessarily related to microarrays only, but I might be wrong. First, I want to thank Robert Gentleman, Mark Kimpel and Mark Reiners for their kind replies. Robert Gentleman kindly
2008 Sep 13
2
moving from aov() to lmer()
Hello, I've used this command to analyse changes in brain volume: mod1<-aov(Volume~Sex*Lobe*Tissue+Error(Subject/(Lobe*Tissue)),data.vslt) I'm comparing males/females. For every subject I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). As aov() provides only type I anovas, I would like to use lmer() with type II, however, I have
2007 Feb 14
1
nested model: lme, aov and LSMeans
I'm working with a nested model (mixed). I have four factors: Patients, Tissue, sex, and tissue_stage. Totally I have 10 patients, for each patient, there are 2 tissues (Cancer vs. Normal). I think Tissue and sex are fixed. Patient is nested in sex,Tissue is nested in patient, and tissue_stage is nested in Tissue. I tried aov and lme as the following, > aov(gene ~ tissue + gender +
2007 Jun 05
1
Can I treat subject as fixed effect in linear model
Hi, There are 20 subjects grouped by Gender, each subject has 2 tissues (normal vs. cancer). In fact, it is a 2-way anova (factors: Gender and tissue) with tissue nested in subject. I've tried the following: Model 1: lme(response ~ tissue*Gender, random = ~1|subject) Model 2: response ~ tissue*Gender + subject Model 3: response ~ tissue*Gender It seems like Model 1 is the correct one
2009 Dec 08
2
automated image processing
Hi, I am looking for a R package which is capable to process and analysis pictures of tissues (stained) in an automatic way. I had a look on biops and EBImage (Bioconductor) but they are not automatic... Did you already use/know a such package ? Thanks, - Martial _________________________________________________________________ Tchattez en direct en en vidéo avec vos amis !
2010 Nov 02
2
multi-level cox ph with time-dependent covariates
Dear all, I would like to know if it is possible to fit in R a Cox ph model with time-dependent covariates and to account for hierarchical effects at the same time. Additionally, I'd like also to know if it would be possible to perform any feature selection on this model fit. I have a data set that is composed by multiple marker measurements (and hundreds of covariates) at different time
2008 Sep 14
2
Help please! How to code a mixed-model with 2 within-subject factors using lme or lmer?
Hello, I'm using aov() to analyse changes in brain volume between males and females. For every subject (there are 331 in total) I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). The data looks like this: Subject Sex Lobe Tissue Volume subect1 1 F g 262374 subect1 1 F w 173758 subect1 1 O g 67155 subect1 1 O w 30067 subect1 1 P g 117981
2011 Nov 15
1
Problem with substr
Hi, everyone When I ran this cript, There is Error in substring(tmp.subject, tmp.end[ex] + 1, tmp.start[ex + 1] - 1) : invalid substring argument(s) Could someone figure out what the problem is? for(i in 1:length(genebody[,1])){ tmp.id<-as.vector(genebody[i,1]) # get gene id tmp.subject<-as.vector(genebody[i,2]) # get gene sequence
2010 Jan 29
1
help on drawing right colors within a grouped xyplot (Lattice)
Hi, I've lost my mind on it... I have to scatterplot two vectors, grouped by a third variable, with two different dimensions according to whether each cell line in the plot is sensitive or resistant to a given drug, and with a different color for each of 9 tissues of origin. Here's what I've done:
2004 Apr 12
1
Very large matrices for very large genome
Hello, I am using R to look at whole-genome gene expression data. This means about 27,000 genes, each with a vector of numbers reflecting expression at different tissues and times. I need to do an all against all co-expression calculation (basically, just calculate Pearson's r for every gene-gene pair). I try to store the result of such a thing in a 27000x27000 matrix, but r seems not to like
2004 Jul 22
0
RE: Comparison of correlation coefficients - Details
Dear Ioannis Thank you very much for pointing me to meta-analysis. Although it may not solve my problem with the normalization, it gives me some other options to display the different correlation coefficients. One possibility is the use of Funnel plots, which are even available in library(rmeta). Another possibility is the use of forest-plots, as implemented in rmeta as metaplot. Sorrowly,
2004 Jan 22
0
problem fitting linear mixed models
Hello, I'm fitting linear mixed models to gene-expression data from microarrays, in a data set where 4608 genes are studied. For a sample of 5 subjects and for each gene we observe the expression level (Intensity) in four different tissues: N, Tp, Tx and M. I want to test whether the expression level is different accross tissues. Between-subject variability is modeled with a random
2006 Dec 07
6
Response To Form Submission Hanging
Hello, I am using Mechanize to post a form to a website. When I do this by hand in my browser the response takes about 35s to come back (it''s a long page full of tables and graphics). When I do this with Mechanize, the server starts to respond and then appears to hang. The obvious conclusion is that my code is wrong but I am reasonably sure that I haven''t altered it
2012 May 11
3
Calculating all possible ratios
I have a data matrix with genes as columns and samples as rows. I want to create all possible gene ratios.Is there an elegant and fast way to do it in R and write it to a dataframe? Thanks for any help. Som. -- View this message in context: http://r.789695.n4.nabble.com/Calculating-all-possible-ratios-tp4627405.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML
2009 Dec 17
1
Help with Merge - unexpected loss of factor level
Hi, Thanks in advance for any advice you can give me, I am very stumped on this problem... I use R every day and consider myself a confident user, but this seems to be an elementary problem.. Outline of problem: I am analysing the results of a study on protein expression in cancer tissues. I have raw intensities from 2 different types of cancer and normal tissue, which can be taken from several
2005 Jul 26
1
tapply t.test
I cannot find in the literature a way to conduct the following t.test on 2 objects, A and B A B col1 col2 col3 col1 col2 col3 Where col(i)'s name is identical in both A and B (they are names of tissues). How do I test (t.test) if each tissue across the object is signifanctly different?? (i'm pretty sure I have to use tapply())
2009 Feb 20
1
lm and aov produce different results for nested fixed-factor anova
Dear R users, I have trouble obtaining the same results for nested Anova with two fixed factors when using lm and aov functions. The formulas are: > e1=aov(y~x/z) > e2=lm(y~x/z) summary(e1) Df Sum Sq Mean Sq F value Pr(>F) x 47 260.0 5.5 18.0088 < 2.2e-16 *** x:z 195 169.6 0.9 2.8318 < 2.2e-16 *** Residuals 14425
2009 Oct 15
0
Setting random effects within a category using nlme
Hello, I will start out with the caveat that I'm not a statistician by training, but have a fairly decent understanding of probability and likelihood. Nevertheless, I'm trying to fit a nonlinear model to a dataset which has two main factors using nlme. Within the dataset there are two Type categories and four Tissue categories, thus giving me 8 datasets in total. The dataset is in
2013 Apr 23
2
Needed: Beta Testers and Summer Camp Students
Greetings. I'm teaching linear regression this semester and that means I write more functions for my regression support package "rockchalk". I'm at a point now were some fresh eyes would help, so if you are a student in a course on regression, please consider looking over my package overview document here: http://pj.freefaculty.org/R/rockchalk.pdf That tells how you can grab
2011 Sep 20
1
A question regarding random effects in 'aov' function
Hi, I am doing an analysis to see if these is tissue specific effects on the gene expression data . Our data were collected from 6 different labs (batch effects). lab 1 has tissue type 1 and tissue type 2, lab 2 has tissue 3, 4,5,6. The other labs has one tissue type each. The 'sample' data is as below: