similar to: non-parametric permutation and signed paired-difference distributions

I have used lme() on data from a between-within subjects experiment. The correct ANOVA table is known because this is a textbook example (Experimental Design by Roger Kirk Chapter 12: Split-Plot Factorial Design). The lme() F-values differ from the known results. Please help me understand why. d<-read.table("kirkspf2.dat",header=TRUE) for(j in 1:4) d[,j] <- factor(d[,j]) ### Make

Hello, I have the following data and I try to properly import it in R and plot the 4th column relative to time 1 2008-249 17:44:17.973 -2.27 00000000: Accepted 2 2008-249 17:44:18.014 -2.28 00000000: Accepted 3 2008-249 17:44:18.064 -2.29 00000000: Accepted 4 2008-249 17:44:18.123 -2.29 00000000: Accepted 5 2008-249 17:44:18.174 -2.29 00000000:

Greetings, I have a question that I'd like to get input on. I have a classic toxicology study where I artificially fertilized and exposed embryos to a chemical and counted defects. In addition, I kept track of male-female pairs that I used to artificially fertilize and generate embryos with. I need to use logistic regression to model the response, but also check that the genetics of the

Hello all! I have a problem with my data in R. When I want to plot the following data, I have a problem with y scale. The maximum value is cc. 10 degrees and in R is about 100. I use this code: fasy<-read.table("gridd1.txt",sep="\t",dec=",",header=T,row.names=1) # here are the years: x <- as.numeric(rownames(fasy)) # extract a series that you want to plot: y

Hello all, I installed Ubuntu 10.10 64 bit on my DELL Studio XPS 1645 notebook, graphic card is a ATI Mobility Radeon HD 4670. I installed also proprietary ati drivers using Ubuntu administration applet, along with Wine 1.2 from package manager. All seems to work properly. This is fglrxinfo output: $ fglrxinfo display: :0.0 screen: 0 OpenGL vendor string: ATI Technologies Inc. OpenGL renderer

Dear list, I want the 1st, 2nd, 5th, and 6th columns of mtcars. After copying them, the columns become numeric class rather than data frame. But, when I copy rows, they data frame retains its class. Why is this? I don't see why copying rows vs columns is so different. > class(mtcars) [1] "data.frame" > head(mtcars) mpg cyl disp hp drat wt qsec vs

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

Hello all, I am trying to minimize a function which contains a double integral, using "nlminb" for the minimization and "adapt" for the integral. The integral is over two variables (thita and radiusb) and the 3 free parameters I want to derive from the minimization are counts0, index and radius_eff. I have used both tasks in the past successfully but this is the first time

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,

I'd like to produce a series of simple line graphs for my methods class that show the three questions used on a repeated survey to make up a particular index. The data frame is: > efficacy.df year complicated havesay dontcare 1 1952 71 68 63 2 1954 NA NA NA 3 1956 64 71 71 4 1958 NA NA NA 5 1960

Hi, all: Two examples are shown below. I want to use the multiple comparison of Dunnett. It succeeded in upper case "example 1". However, the lower case "example 2" went wrong. In "example 2", the function pmvt return NaN, so I cannot show this simtest result. Is there any solution? (I changed the variable "maxpts" to a large number in front of the

Dear all, What is the quickest and most efficient way to diff two data frames, so as to obtain a vector of indices (or logical) for rows/columns that differ in the two data frames? For example, > Xe <- head(mtcars) > Xf <- head(mtcars) > Xf[2:4,3:5] <- 55 > all.equal(Xe, Xf) [1] "Component 3: Mean relative difference: 0.6863118" [2] "Component 4: Mean relative

Doe anyone know of a way to print nice-looking, printer-friendly tables directly in the R plot window? This would be very handy for examining preliminary results from frequently used routines. I've hunted for this with no luck. All anyone seems to do is export text files to excel for formatting, or use the print(bla) function which just calls the numbers at the command line. There must be

Hi everyone, I'm having some difficulty getting "simple effects" for the ols() function in the rms package. The example below illustrates my difficulty -- I'll be grateful for any help. #make up some data exD <- structure(list(Gender = structure(c(1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L), .Label = c("F", "M"), class = "factor"),

Hi everybody, I'm trying to construct contrasts for an ANOVA to determine if there is a significant trend in the means of my groups. In the following example, based on the type of 2x3 ANOVA I'm trying to perform, does the linear polynomial contrast generated by contr.poly allow me to test for a linear trend across groups? doi=data.frame( Group=c( rep(1, 5), rep(2, 5), rep(3, 5),

##I want to remove the rows where the row sums are zero and this is as far as I have gotten ffg <- (structure(list(CD = c(0, 0, 0, 0, 3.125, 0, 0, 0, 0, 1.6, 3.125, 0, 0, 6.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0,

Greetings, A couple general questions regarding the use of splines to interpolate depth profile data. Here is an example of a set of depths, with associated attributes for a given soil profile, along with a function for calculating midpoints from a set of soil horizon boundaries: #calculate midpoints: mid <- function(x) { for( i in 1:length(x)) { if( i > 1) { a[i] = (x[i] -

Hi, and thanks in advance for any assistance, I'm new to R and to this mailing list, and am having trouble with the * persp()* function. I've got a matrix (z) of values for various combinations of x and y, each of which is a set of (0, 5, 10, 15, 20). But when I try * persp(x,y,z)*, I get an "*invalid z argument*" error, and when I try simply *persp(z)*, R returns an

Dear all. I have some data and I seek the way to start their evaluation. The values are from survey of different persons and their opinion about various methods (metoda) and instrument (uzel). I am not sure where to start. I would like to end with combination of method (metoda) and instrument (uzel) sorted to let say three categories according to knowledge (znalost) and influence (vliv)

I don't have Kirk but with your data in file "Kirk.txt" in the working directory, here is how I would do it. --- > Kirk <- read.table("Kirk.txt") > names(Kirk) [1] "subject" "A" "B" "C" "response" > for(j in 1:4) Kirk[,j] <- factor(Kirk[,j]) ### Check this! > fm <- aov(response ~