similar to: Is it possible with two random effects in lme()?

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Hola. Hay alguna función que haga un Friedman test (digamos 4 tratamientos o tiempos relacionados/dependientes) y que después haga una comparación de un tratamiento contra el resto, digamos el primero, como un contratase simple, o un Dunnett? o simplemente ¿como hago un Dunnett para unos tratamientos relacionados? -- Antonio M [[alternative HTML version deleted]]

Hi: I'm using function lmer from package lme4, and I get this message: " There were 12 warnings (use warnings() to see them)" So I checked them: Warnings 1 to 11 said: 1: optim returned message ERROR: ABNORMAL_TERMINATION_IN_LNSRCH in: "LMEoptimize<-"(`*tmp*`, value = structure(list(maxIter = 50, ... and Warning 12 said: 12: IRLS iterations for glmm did

Dear professors and collegues I need to perform a analysis of dates from a nested experimental design. From "Bioestatical Analysis" of Zar "Bimetry of Sokal" & Rohlf "Design and Analysis of Experiments" of Montgomery I have: Sum (mean(x)_i - mean(x)_T)2 / (a-1) -> var(epsilon) + n sigma2_B + n b (sum alfa_i)2 / (a-1) Sum (mean(x)_ij - mean(x)_i)2 /

Hi, I'm building Tukey's table using qtukey function. It happens that I can't get the values of Tukey's one degree of freedom and also wanted to eliminate the first column. The program is: Trat <- c(1:30) # number of treatments gl <- c(1:30, 40, 60, 120) # degree freedom tukval <- matrix(0, nr=length(gl), nc=length(Trat)) for(i in

Hi, I run a maanova analysis and found this message error: Error in ma.svd(X, 0, 0) : 0 extent dimensions I did a google search and found this: \item ma.svd: function to compute the sigular-value decomposition of a rectangular matrix by using LAPACK routines DEGSVD AND ZGESVD. \item fdr: function to calculate the adjusted P values for FDR control. I did a search for LAPACK and

Hi all, I'm working with a dataset from 10 treatments, each treatment with 30 subjects, each subject measured 5 times. The plot of the dataset suggests that a 3-parameter logistic could be a reasonable function to describe the data. When I try to fit the model using gnls I got the message 'Step halving factor reduced below minimum in NLS step'. I´m using as the initial values of the

Hi, I used the commands below to make Hartley's table, but some values are NA. require(SuppDists) trat = seq(2, 15, 1) gl = seq(2, 40, 1) har = matrix(0, nr=length(gl), nc=length(trat)) for(i in 1:length(gl)) for(j in 1:length(trat)) har[i,j] <- qmaxFratio(.95, df=gl[i], k=trat[j]) rownames(har) <- gl colnames(har) <- trat head(har) The output (head): 2

Jesus how do u post something, it always comes back :( -----Original Message----- From: Rend, Jon (Jon) % [mailto:rend@agere.com] Sent: Tuesday, October 29, 2002 8:05 AM To: 'samba@lists.samba.org' Subject: [Samba] (no subject) On friday we changed our smb.conf file to test the security model that uses DOMAIN authenticacion. It worked fine testing two seperate usernames from Multiple

Hi, I did the analysis of variance of a split-plot and the effect of treatment was significant. I would like compare treatment means using Tukey. I can't extract the mean square to apply HSD.test to use in agricolae package. anava = aov(ganhos ~ Blocos + Trat*Supl + Error(Blocos/Trat)) names(anava) summary(anava) require(agricolae) HSD.test(ganhos, Trat, df, MSerror, alpha = 0.05)

Hi, I have data on stomach contents. Possible prey species are in the hundreds, so a list of prey codes has been in used in many labs doing this kind of work. When comes time to do analyses on these data one often wants to regroup prey in broader categories, especially for rare prey. In SAS you can nest a large number of "if-else", or do this more cleanly with "select"

Hi, I try to plot bars with different colours in a barchart graphic. My idea is make that all X-Levels from trat var with different colour (grey scale). I search for a solution but dont find any. Any help? Thanks dados <- structure(list(Medias = c(0.994169096209855, 0.99416342412449, 0.974683544303797, 0.954430379746835, 0.669047619047619, 0.999999998475569, 0.994163424124514,

I'm new using R im trying to do a tukey test, but when i see the results the p value results in NA im guessing its because i have missing values but im not sure how to fix it AnovaModel.2 <- aov(area ~ trat, data=apilados) > summary(AnovaModel.2) Df Sum Sq Mean Sq F value Pr(>F) trat 4 11847 2961.76 9.9905 1.500e-06 *** Residuals 76 22531 296.46

Is there a way to map NT names to UNIX names when they are not the same. 95% of our are which is great but we have a few that are different. For example, we have NT user "bigboy" who's Unix account is "smallboy", how can I make an association, oh learned 1's. Thanks, Jon :-) agere systems Office 651-675-3064* 1230 Northland DriveF Cell Phone

Hi R experts :) I'm trying to carry out a survival model on my data, but I am unsure of whether it's appropriate or if I should do something specific in regards to hazard. My data is time to death by predator where I have 8 prey and one predator in the setting. This means that two prey can't possibly die at the same time and I can't quite get my head around how to include this in

Hi, I'm trying to move to R the last few data handling routines I was performing in SAS. I'm working on stomach content data. In the simplified example I provide below, there are variables describing the origin of each prey item (nbpc is a ship number, each ship may have been used on different trips, each trip has stations, and individual fish (tagno) can be caught at each

Hi, How I could improve this graphic? http://www.divshare.com/download/10754700-f81 I would like to write groups labels in each panel and override the labels from object. I am try this code: xyplot(percentagem.mortos~tempo|trat, data=bio.ens, type="a", ? ? ? auto.key=list(points=FALSE, lines=TRUE, columns=3), ? ? ? ylim=c(0,100),scales = list(x = list(at = c(48, 72, 96), labels ? ?

Hi, I wonder if anyone can help me with specifying a right model for my analysis. I am a beginner to lme methods and though have spent already many hours studying from various books an on-line helps, I was unfortunately not able to find a solution to my problem on my own. Data structure: I studied escape behavior of three species of a prey to a predator. The prey specimens (many) were in a

I'm fairly new to R, and I'm trying to write out a population model that satisfies the following; the system consists of s species, i= 1, 2,...,s network of interactions between species is specified by a (s x s) real matrix, C[i,j] x[i] being the relative population of the "ith" species (0 =< x[i] =< 1, sum(x[i]=1) the evolution rule being considered is as follows;

Hi all, I have a little problem. I make an weibull survival analysis using the survival package. It,s OK, them I have the functions. I plot this funcions with curve(). I want to make a plot with the real survival points (proportion of alive x time) and them add the curves to points. I have the time to dead, the censor data and my trataments. To analysis the model is: model1 <-