similar to: Probability for ANOVA

Hi there, I have some data which are convenient to enter as lists. For example: t1<-list(fname="animal1",testname="hyla",dspkr="left",res1=39.7,res2=15.0) t2<-list(fname="animal1",testname="bufo",dspkr="left",res1=14.4,res2=56.1)

Hi all, I have a simple data frame of three columns - one of numbers (really a categorical variable), one of dates and one of data. Imagine: collar date data 1 01/01/2013 x 2 02/01/2013 y 3 04/01/2013 z 4 04/01/2013 a 5 07/01/2013 b The 'collar' is a GPS collar that's been worn by an animal for a certain amount of time, and then may have been worn by a different animal after

Hi! I use simtest fonction of multcomp package to compile a Dunnett's test. I have 10 treatments and one control group, so i create a matrix with: m<-matrix(0,10,11) m[1,1]<--1 m[1,2]<-1 m[2,1]<--1 m[2,3]<-1 m[3,1]<--1 m[3,4]<-1 m[4,1]<--1 m[4,5]<-1 m[5,1]<--1 m[5,6]<-1 m[6,1]<--1 m[6,7]<-1 m[7,1]<--1 m[7,8]<-1 m[8,1]<--1 m[8,9]<-1

Hi all! How to retrieve the levels number of a factor object? See this code: groups<-gl(4,10) I want to retrieve the number of levels (4) of my object "groups" I tried groups.levels but this don't work Thanks Laurent Houdusse Analyste Programmeur

Hi all! I 'm beginner and i develop a bio-application with VB and i need some statistic functions! could i calculate StdError, CoeffOfVariance, SumSquared with R langage? if yes, what are functions to use? I need also to use ANOVA and t-test... Thanks for your help! Laurent Houdusse Analyste Programmeur

Hi, I'm a newbie and i am unable to use lillie.test in nortest I have a message: "Couldn't find function "lillie.test" I am under windows2000 with R1.8.1 nortest is listed with .packages(TRUE) How to do to use lillie.test function? Laurent Houdusse Analyste Programmeur

I don't know if this is the best place to post this question but I will try anyway. I have two experiements for which I use one-way matched-randomized ANOVA for the analysis and I would like to compare different treatments in the two experiments. The only common group in the two experiments are the controls. Is there any ANOVA design that allows me to make this comparison taking into

Hi R help forum, I have a simple data frame of four columns - one of numbers (really a categorical variable), one of dates and one of data. I have over 500,000 data points to work with, spread over 40 files, each named after a different animal. These are contact data recorded by proximity loggers over two years between the animals of the file name and collars being worn by other animals. The

Hi, I use ks.test or lillie.test to verify a normal distribution. It's performed for a group My users use SigmaStat software and a One Way ANOVA on several groups In the result page there is a probability value to determine if Normality test is failed or passed So, how can i retrieve this probability value on several groups? Is there another function in R to verify normality on several

Hi, I have been struggling with this problem for some time now. Internet, books haven't been able to help me. ## I have factorial design with counts (fruits) as response variable. > str(stubb) 'data.frame': 334 obs. of 5 variables: $ id : int 6 23 24 25 26 27 28 29 31 34 ... $ infl.treat : Factor w/ 2 levels "0","1": 2 2 2 2 1 1 1 2 1 1 ... $ def.treat :

Hi all, Two questions: 1. Is there a way to evaluate models from lmer() with a poisson distribution? I get the following error message: library(lme4) lmer(tot.fruit~infl.treat+def.treat+(1|initial.size),family=poisson)->model plot(fitted(model),resid(model)) Error: 'resid' is not implemented yet Are there any other options? 2. Why doesn't the function estimable() in gmodels

I have some disconnected boundary data from a finite element ocean model and I'd like to make a plot. Maptools looks promising, but since my data is not in a shapefile or a map, I'm unclear on what the best way to approach the problem. >geom[1:10,] lon lat depth 1 -75.42481 35.58192 16.172 2 -75.40726 35.58567 18.045 3 -75.41351 35.60312 17.333 4 -75.38888 35.58959

Hi all, I don't know if anyone has any thoughts on this. I have been trying to move from SAS Proc Mixed to R nlme and have an unusual result. I have several subjects measured at four timepoints. I want to model the within-subject correlation using an autoregressive structure. I've attached the R and SAS code I'm using along with the results from SAS. With R lme I get an estimate of

Hi, I want to retrieve a value in the Dunnett's tables. I know the comparisons type, the percent of level,the number of traitments and the degrees of freedom. Is there a function to retrieve this value with this? Laurent Houdusse Analyste Programmeur

Hi everyone, upon login windows reports: "Windows cannot create profile directory \\fw\profiles\leon.pds. You will be logged on with a local profile only. Changes to the profile will not be propagated to the server." Then it says: "Windows cannot find the local profile and is logging you on with a temporary profile. Changes you make..." looked all over now, tested variations

Dear all, Does any one knows why should I get the following error message, when trying to do a simple data.frame?? DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS p,DSSp,Slope, CanDens,NearestSp) Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, : arguments imply differing number of rows: 202, 0 The data I am using

Dear all, The following is a example that I run and hope to get a linear model. However, I find the lm() can not give correct coefficients for the linear model. I hope it's just my own mistake. Please help. TIA. Regards, Jinsong > x [1] 3.760216 3.997288 3.208872 3.985417 3.265704 3.497505 2.923540 3.193937 [9] 3.102787 3.419574 3.169374 2.928510 3.153821 3.100385 3.768770 3.610583

Dear Mr. and Mrs. I'm very grateful for these software and this list. My question is: when a use linear multiple regression (lm()) for my data, abundance ichthyoplankton ~ salinity + temperature + month of the year(f1 is a factor: 1 for january, 2 for february, ..., 12 for december), the summary() of results is ... Coefficients: Estimate Std. Error t value Pr(>|t|)

I would suggest stats::glm() should set "converged" to FALSE in the return value in a few more situations. I believe the current returned converged == TRUE can be needlessly misleading when the algorithm has clearly failed (and the algo even issued a warning, but the returned structure claims all is well). In particular there are pathological inputs which cause the residual deviance to

When I use the hills data in Maindonald's text (below) and apply coplot(time ~ distance | climb, data=hills, overlap=0.0, number=3) the graphs do not appear to line up with the conditional axis climb. Is this a bug or am I missing something as an R newbie? Thanks, Bob Abugov distance climb time Greenmantle 2.5 650 16.083 Carnethy 6.0 2500