search for: livers

Displaying 20 results from an estimated 49 matches for "livers".

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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 <-
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
2005 Sep 07
1
FW: Re: Doubt about nested aov output
Ronaldo, Further to my previous posting on your Glycogen nested aov model. Having read Douglas Bates' response 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
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:
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
2003 Dec 01
0
No subject
Perhaps you can see somethign I can't - or perhaps there is a better way for me to get information for you ? Let me know if there is as this server is not live yet... All the best, Noel NB ATTACHMENTS REMOVED FOR LIST POSTING Domain/network info: Domain = UK Win2000 DC (192.168.5.4) = BRAIN Live Samba server 2.2.3a (192.168.5.5) = BELLY New Samba server 2.2.3a
2007 May 03
4
Survival statistics--displaying multiple plots
Hello all! I am once again analyzing patient survival data with chronic liver disease. The severity of the liver disease is given by a number which is continuously variable. I have referred to this number as "meld"--model for end stage liver disease--which is the result of a mathematical calculation on underlying laboratory values. So, for example, I can generate a Kaplan-Meier plot
2006 Sep 03
2
Running cox models
Hi, I'm reading van Belle et al "Biostatistics" and trying to run a cox test using a dataset from: http://faculty.washington.edu/~heagerty/Books/Biostatistics/chapter16.html (Primary Biliary Cirrhosis data link at top of the page), I'm using the following code: --------------- start of code library(survival) liver <-
2010 Sep 24
1
Fitting GLMM models with glmer
Hi everybody: I?m trying to rewrite some routines originally written for SAS?s PROC NLMIXED into LME4's glmer. These examples came from a paper by Nelson et al. (Use of the Probability Integral Transformation to Fit Nonlinear Mixed-Models with Nonnormal Random Effects - 2006). Firstly the authors fit a Poisson model with canonical link and a single normal random effect bi ~ N(0;Sigma^2).The
2004 Aug 29
0
good news - regenerating of the heart, liver, kidneys and other organs
dienspligtige.rochester etilleta~jpl-gdss roll-play What can we supply? 221 med,ications in 41 categories that relieve the pain. reduce the extra kilos and cease the symptom of Allergy, with presc"^"ript"'"ion from a licensed online ph~armacy. dr^ugs from canada & 0~v'er_night d,eliv`er http://ci.s.werthebestrx.info/track.asp?cg=ta&c=info `That must be a
2011 Mar 14
0
Non-constancy of variances in mixed model.
Hi, I've been doing an experiment, measuring the dead-zone-diameters of bacteria, when they've been grown with paper diffusion disks of antimicrobial. There are two groups, or treatments - one is bacteria that have been cultured in said antimicrobial for the past year, the other group is of the same species, but lab stock and has not gone had any prior contact with the antimicrobial.
2004 Jun 11
1
ROC for threshold value, biometrics
Hello, I am just a beginner of R 1.9.0. I try to construct a predictive score for the development of liver cancer in cirrhotic patients. So dependant variable is binanry (cancer yes or no). Independant variables are biological data. The aim is to find out a cut-off value which differentiate (theoratically) from normal to pathological state for each biological data. How can I step in procedue to
2005 Oct 20
0
lmer and grouping fators
Hi, I make this model using lme m.lme <- lme(Glycogen~Treatment,random=~1|rTrt/Liver) How to make this using lmer? I try > m.lmer <- lmer(Glycogen~Treatment+(1|rTrt/Liver)) Erro em lmer(Glycogen ~ Treatment + (1 | rTrt/Liver)) : entry 0 in matrix[0,0] has row 2147483647 and column 2147483647 Al??m disso: Mensagem de aviso: / not meaningful for factors in: Ops.factor(rTrt, Liver)
2008 Jul 14
1
Tissue specific genes by ANOVA?
Hello, unfortunately I have I big problem I can't solve. I have to analyse if a gene is tissue specific. For example for the gene xyz I have following expression values: Heart Liver Brain 8.998497 10.013561 12.277407 9.743556 10.137574 11.033957 For every tissue I have two values from two different experiments. Now I want to test if Heart is significant higher
2011 May 20
1
How to do covariate adjustment in R
Hi, I have a question about how to do covariate adjustment. I have two sets of 'gene expression' data. They are from two different tissue types, 'liver' and 'brain', respectively. The purpose of my analysis is to compare the pattern of the whole genome 'gene expression' between the two tissue types. I have 'age' and 'sex' as covariates. Since
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:
2005 Sep 08
1
FW: Re: Doubt about nested aov output
Your response nicely clarifies a question that I've had for a long time, but which I've dealt with by giving each subject a unique label. Unless I'm missing something, both techniques should work as the toy example below gives exactly the same output in all 3 cases below (forgetting about the convergence problem). Would there be a reason to prefer labeling the levels one way or
2005 Jun 02
0
How to calculate the correct SE in a nested or spliplot anova?
Hi! How to calculate the correct SE of mean in a nested or spliplot anova? Nested example: --------------------- m <- aov(Glycogen~Treatment+Error(Treatment/Rat/Liver)) > m Call: aov(formula = Glycogen ~ Treatment + Error(Treatment/Rat/Liver)) Grand Mean: 142.2222 Stratum 1: Treatment Terms: Treatment Sum of Squares 1557.556 Deg. of Freedom 2 Estimated
2005 Aug 30
2
Doubt about nested aov output
Hi, I have two doubts about the nested aov output. 1) I have this: > anova.ratos <- aov(Glicogenio~Tratamento+Error(Tratamento/Rato/Figado)) > summary(anova.ratos) Error: Tratamento Df Sum Sq Mean Sq Tratamento 2 1557.56 778.78 Error: Tratamento:Rato Df Sum Sq Mean Sq F value Pr(>F) Residuals 3 797.67 265.89 Error: Tratamento:Rato:Figado
2011 Sep 15
1
Questions on 'lme' function, urgent!
Hi Dear all, I have some gene expression data samples from different tissue types ----------------------------------------------- - 120 samples from blood (B) - 20 samples from Liver (L) - 15 samples from Kidney (K) - 6 samples from heart (H) ----------------------------------------------- All the samples are from different individuals, so there are in total 161 individuals from which the DNA was