similar to: Comparing treatments in Multivariate Analysis

Hi R-users I'm working with a data.frame of 40000 x 10, for which I need to apply the "split" function. The result is very long and cannot be stored in a variable due to memory exceeding. I've tried to send the result directly to a file through sink(filename) function, but the problem still occurs. Does anyone have an idea to solve this issue? > dim(dados) [1] 40000 10

Hi R-users Does anybody know if there are functions or packages in R for sphericity tests like Bartlett's or Mauchly's? Thanks! __________________________________________________________ Eng. Agr., M.Sc. Eduardo Dutra de Armas __________________________________________________________ Centro de Energia Nuclear na Agricultura (CENA/USP) Laboratório de Ecotoxicologia Av.Centenário 303,

Dear R helpers I have a daily rainfall dataset of 5 stations, but the time-series are of different lengths. Three stations measured precipitation from 1917 to 2004, one from 1930 to 1979, and other from 1975 to 1998. I'd like to know how to analyse if rainfall is similiar at all stations. Is it possible to compare time-series like these? Best Regards!

Hi R-users Does anyone know how to increase the resolution of plots to be exported? I'm exporting some plots but the maximum resolution that I get is 96 dpi. I want to get files with 300dpi. Thanks! __________________________________________________________ Eng. Agr., M.Sc. Eduardo Dutra de Armas __________________________________________________________ Centro de Energia Nuclear na

Hi R-users I recently downloaded RdbiPgSQL 1.8.0 and Rdbi 1.8.0 from Bioconductor to be installed under R 2.4.1. When requiring RdbiPgSQL an error message is showed as follows: > require(RdbiPgSQL) Loading required package: RdbiPgSQL Error in library(package, lib.loc = lib.loc, character.only = TRUE, logical = TRUE, : ‘RdbiPgSQL’ is not a valid package – installed <

Hi R-users I'm trying to do multivariate analysis of variance of a experiment with 3 treatments, 2 variables and 5 replicates. The procedure adopted in SAS is as follow, but I'm having difficulty in to implement the contrasts for comparison of all treatments in R. I have already read manuals and other materials about manova in R, but nothing about specific contrasts were found in them,

Hello R listing, I did two-way anova on lm. Further question the investigator interested in is what two treatments are different? I am looking for a command which could do pairwise comparison for every treatment. Could anyone help me out? Thanks a bunch Kevin

Dear All, I would like to find something ( references, code,..) to implement a comparison of three treatments in an observational study using the 'Propensity Score'. Any help is much appreciated. Thanks! Giovanni -- dr. Giovanni Parrinello Department of Biotecnologies Medical Statistics Unit University of Brescia Viale Europa, 11 25123 Brescia email: parrinel at med.unibs.it Phone:

Hi, I am comparing three treatments. The data come from a longitudinal study, and for each treatment I have only 1 case, on which the observations across 20 years are made. My main aim is to compare the three treatments, but the effect of time is of interest as well. Which of the many R functions should I use for that purpose? I applied the aov function and received this:

Hi Folks, I'm a bit puzzled by the following (example): N<-factor(sample(c(1,2,3),1000,replace=TRUE)) unique(N) # [1] 3 2 1 # Levels: 1 2 3 So far so good. Now: contrasts(N)<-contr.treatment(3, base=1, contrasts=FALSE) contrasts(N) # 1 2 # 1 1 0 # 2 0 1 # 3 0 0 whereas: contr.treatment(3, base=1, contrasts=FALSE) # 1 2 3 # 1 1 0 0 # 2 0 1 0 # 3 0 0 1 contr.treatment(3, base=1,

Hi there, I need some help to figure out what is the proper model in survival analysis for my data. Subjects were randomized to 3 treatments in trial 1, some of them experience the event during the trial; After period of time those subjects were randomized to 3 treatments again in trial 2, but different from what they got in 1st trial, some of them experience the event during the 2nd trial (I

I have a dataframe with several different treatment variables, and would like to calculate the mean and standard deviation of the replicates for each day and treatment variable. It seems like it should be easy, but I've only managed to do it for one treatment at a time using subset and tapply. Here is an example dataset: > `exampledata` <- structure(list(day = c(1L, 1L, 1L, 1L, 1L,

Hi, I am a complete newcomer to R and although I can plot standard box-plots I am struggling with this... I have two treatments - A & B, and 2 variables 1 & 2. I want to compare boxplots of variable 1 with variable 2 for each treatment. I would also like them to all be on the same graphic. I would like treatment to be on the x axis (A and B) and above A and B have their corresponding

Hi, I have searched the archives and can't quite confirm the answer to this. I appreciate your time... I have 4 treatments (fixed) and I would like to know if there is a significant difference in metal volume (metal) between the treatments. The experiment has 5 blocks (random) in each treatment and no block is repeated across treatments. Within each plot there are varying numbers of