search for: rat

Displaying 20 results from an estimated 551 matches for "rat".

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2006 Aug 30
1
lmer applied to a wellknown (?) example
Dear all, During my pre-R era I tried (yes, tried) to understand mixed models by working through the 'rat example' in Sokal and Rohlfs Biometry (2000) 3ed p 288-292. The same example was later used by Crawley (2002) in his Statistical Computing p 363-373 and I have seen the same data being used elsewhere in the litterature. Because this example is so thoroughly described, I thought it would be...
2008 Apr 04
1
lme4: How to specify nested factors, meaning of : and %in%
Hello list, I'm trying to figure out how exactly the specification of nested random effects works in the lmer function of lme4. To give a concrete example, consider the rat-liver dataset from the R book (rats.txt from: http://www.bio.ic.ac.uk/research/mjcraw/therbook/data/ ). Crawley suggests to analyze this data in the following way: library(lme4) attach(rats) Treatment <- factor(Treatment) Rat <-factor(Rat) Liver<-factor(Liver) m1<-lmer(Glycogen~...
2003 Mar 21
2
Trying to make a nested lme analysis
Hi, I''m trying to understand the lme output and procedure. I''m using the Crawley''s book. I''m try to analyse the rats example take from Sokal and Rohlf (1995). I make a nested analysis using aov following the book. > summary(rats) Glycogen Treatment Rat Liver Min. :125.0 Min. :1 Min. :1.0 Min. :1 1st Qu.:135.8 1st Qu.:1 1st Qu.:1.0 1st Qu.:1 Median :141.0...
2005 Sep 07
1
FW: Re: Doubt about nested aov output
...nse and Reflected on his lmer analysis output of your aov nested model example as given.The Glycogen treatment has to be a Fixed Effect.If a 'treatment' isn't a Fixed Effect what is ? If Douglas Bates' lmer model is modified to treat Glycogen Treatment as a purely Fixed Effect,with Rat and the interaction Rat:Liver as random effects then-- > model.lmer<-lmer(Glycogen~Treatment+(1|Rat)+(1|Rat:Liver)) > summary(model.lmer) Linear mixed-effects model fit by REML Formula: Glycogen ~ Treatment + (1 | Rat) + (1 | Rat:Liver) AIC BIC logLik MLdeviance REMLdeviance...
2005 Feb 10
1
rats in survival package
Dear R-listers, Does anybody know what is the correct source of "rats" dataset in survival package? The help gives the following information: Rat data from survival5 Description: 48 rats were injected with a carcinogen, and then randomized to either drug or placebo. The number of tumors ranges from 0 to 13; all rats were censored at 6 month...
2003 Feb 13
1
fixed and random effects in lme
Hi All, I would like to ask a question on fixed and random effecti in lme. I am fiddlying around Mick Crawley dataset "rats" : http://www.bio.ic.ac.uk/research/mjcraw/statcomp/data/ The advantage is that most work is already done in Crawley's book (page 361 onwards) so I can check what I am doing. I am tryg to reproduce the nested analysis on page 368: model<-aov(Glycogen~Treatment/Rat/Liver + Error(Tr...
2010 Aug 22
2
coxme AIC score and p-value mismatch??
...new to R and AIC scores but what I get from coxme seems wrong. The AIC score increases as p-values decrease. Since lower AIC scores mean better models and lower p-values mean stronger effects or differences then shouldn't they change in the same direction? I found this happens with the data set rats as well as my own data. Below is the output for two models constructed with the rats data set. >library(survival) >data(rats) > str(rats) 'data.frame': 150 obs. of 4 variables: $ time : int 101 104 104 77 89 88 104 96 82 70 ... $ tumor : int 0 0 0 0 0 1 1 1 0 1 ... $ t...
2005 Sep 08
1
FW: Re: Doubt about nested aov output
...) subj <- gl(5, 1, 15) dd <- data.frame(y = y, cond = cond, obs = obs, subj = subj) l1 <- lmer(y~cond + (1|cond:obs), dd) l2 <- lmer(y~cond + (1|cond:subj), dd) l3 <- lmer(y~cond + (1|obs), dd) Douglas Bates a ??crit: The difference between models like lmer(Glycogen~Treatment+(1|Rat)+(1|Rat:Liver)) and lmer(Glycogen~Treatment+(1|Treatment:Rat)+(1|Treatment:Rat:Liver)) is more about the meaning of the levels of "Rat" than about the meaning of "Treatment". As I understood it there are three different rats labelled 1. There is a rat 1 on treatment 1 and a...
2010 Apr 18
2
plotting pca of samples in different colors
Hi! All, I am working on a dataset 'rat' with dimension 20500x363. I have calculated pca of samples (columns). Now I am trying to plot first two principle components with specified columns in different color. I have done following so far: > dim(rat) [1] 20500 363 >#specifying columns to be colored in red > a1=colnames(rat...
2007 Dec 20
1
hierarchical linear models, mixed models and lme
Dear R-users, I am trying to analyse the data of the box 10.5 in the Biometry from Sokal and Rohlf (2001) using R. This is a three-level nested anova with equal sample size : 3 different treatments are compared ; 2 rats (coded 1 or 2) / treatment are studied ; 3 preparations (coded 1, 2 or 3) / rats are available ; 2 readings of the glycogen content / preparations are realised. Treatment is fixed whereas Rats (nested in Treatment) and Prep (nested in Rats) are random effects. According to a previous discus...
2010 Oct 04
2
Plot for Binomial GLM
Hi i would like to use some graphs or tables to explore the data and make some sensible guesses of what to expect to see in a glm model to assess if toxin concentration and sex have a relationship with the kill rate of rats. But i cant seem to work it out as i have two predictor variables~help?Thanks.:) Here's my data. > rat.toxic<-read.table(file="Rats.csv",header=T,row.names=NULL,sep=",") > attach(rat.toxic) > names(rat.t...
2008 Jul 31
4
Identifying common prefixes from a vector of words, and delete those prefixes
For example, c("dog.is.an.animal", "cat.is.an.animal", "rat.is.an.animal"). How can I identify the common prefix is ".is.an.animal" and delete it to give c("dog", "cat", "rat") ? Thanks _________________________________________________________________ [[alternative HTML version deleted]]
2013 Feb 20
0
Bayesian mixing model
Fellow R users, I'm using the BCE {BCE} function to run a Bayesian sediment mixing model. The aim is to find the optimum % contribution from each of the 4 source areas that can yield the target geochemistry. I have geochemistry for 4 source areas called Rat: Rat<-read.table(text="CaO MgO Na2O Al2O3 Topsoils 2.511250 0.7445500 0.7085500 14.10375 ChannelBanks 55.021500 0.8665000 0.3045000 10.19800 FieldDrains 17.958221 0.9415394 0.2979383 14.68013 RoadRunoff 9.177297 1.9034304 0.4618634 22.22206", header=TRUE) ...an...
2012 May 19
2
Loading the stupid dataset--help!!!
I am using the following: library(RODBC) chan = odbcConnectExcel("rats-lda") rats.lda = sqlFetch(chan, "data") close(chan) And getting the following error message: > library(RODBC) Error in library(RODBC) : there is no package called ?RODBC? > chan = odbcConnectExcel("rats-lda") Error: could not find function "odbcConnectExcel&qu...
2006 Aug 02
5
Finding the position of a variable in a data.frame
...w do I find the coordinates. I can find the row by doing a subset on the data.frame but how do I find out here "blaw " is in columns without manually counting them or converting names(Df) to a list and reading down the list. Simple example cat <- c( 3,5,6,8,0) dog <- c(3,5,3,6, 0) rat <- c (5, 5, 4, 9, 0) bat <- c( 12, 42, 45, 32, 54) Df <- data.frame(cbind(cat, dog, rat, bat)) Df subset(Df, bat >= 50) ----results cat dog rat bat 5 0 0 0 54 Thus I know that my target is in row 5 but how do I figure out where 'bat' is? All I want to do is be ab...
2010 Jul 08
0
ANOVA-Formula
Hi, I have taken one microarray experiment and trying to implement same statistical measures what they have done.I have taken datasets from GEO platform with accession number GSE1557. In the experiment,about half of double transgenic rats (dTGR) over-expressing the human renin and angiotensinogen genes die by age 7 weeks of terminal heart failure (THF); the other (preterminal) half develops cardiac damage, but survives to week 7. The aim of the study was to elucidate the difference in cardiac gene expression of dTGR with THF compar...
2009 Mar 09
2
bug of *switch* function
...ing. The version I use is R version 2.9.0 Under development (unstable) (2009-02-21 r47969) here is the output: > organism="human" > species <- switch(organism, human <- "Hs", fly <- "Dm", mouse <- "Mm", rat <- "Rn", yeast <- "Sc" ) species <- switch(organism, + human <- "Hs", + fly <- "Dm", + mouse <- "Mm", + rat <- "Rn", + yeast <- "Sc" + ) > species [1] "Hs" > organis...
2007 Jan 26
0
[BioC] problem with biomaRt getHomolog function
...ease) 1-(317)-536-2730 FAX -----Original Message----- From: Steffen Durinck [mailto:durincks at mail.nih.gov] Sent: Friday, January 26, 2007 9:24 AM To: Kimpel, Mark William Cc: bioconductor at stat.math.ethz.ch Subject: Re: [BioC] problem with biomaRt getHomolog function Hi Mark, I think the rat entrezgene id 613226 is a recently added entrezgene id and is not yet available in Ensembl. Ensembl updates every two months and the last update of entrezgene id 613226 appears to be December 26 of 2006. So this might be the reason. Also I would suggest you use the developmental version of bio...
2006 Mar 13
2
Error Message from Variogram.lme Example
When I try to run the example from Variogram with an lme object, I get an error (although summary works): R : Copyright 2005, The R Foundation for Statistical Computing Version 2.2.1 (2005-12-20 r36812) ISBN 3-900051-07-0 ... > fm1 <- lme(weight ~ Time * Diet, BodyWeight, ~ Time | Rat) Error: couldn't find function "lme" > Variogram(fm1, form = ~ Time | Rat, nint = 10, robust = TRUE) Error: couldn't find function "Variogram" > library(nlme) > fm1 <- lme(weight ~ Time * Diet, BodyWeight, ~ Time | Rat) > Variogram(fm1, form = ~...
2006 Mar 06
1
P-values from survreg (survival package) using a clusterterm
...ch estimator using (here I guess) an emperical (unstructered/exchangeable?) ICC. Shouldent it be, at least to some extend, comparable to the robust z-test, for rx : 2*pnorm(-0.239/0.0816)=0.0034 ? Any help/hints are appreciated. Steen and R 2.2.1, survival 2.21 on win XP. library(survival) data(rats) marginal.model <- survreg(Surv(time, status) ~ rx + cluster(litter), rats ) summary(marginal.model) > library(survival) > data(rats) > marginal.model <- survreg(Surv(time, status) ~ rx + cluster(litter), rats ) > summary(marginal.model) Call: survreg(formula = Surv(time, sta...