similar to: Mixed models with missing data

hi,? I'm working on a research project where we're looking at the changing resonances in femur bones during hip replacement operations. basically, I've got a spreadsheet with one column listing frequencies in 5Hz bands and 3 columns showing the amplitude of that frequency when the bone is loose, medium to tight (referring to the tension of the reamer/chisel creating a cavity for the

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Dear list, I'm quite confused when interpreting results from a mixed linear model. For example, working on Iris data frame, I want to know the effect of species on slope of the model "Petal.Length~Sepal.Length" I write this : data(iris) reg01 <- lm(Petal.Length~Sepal.Length + Sepal.Length:Species, data=iris) summary(reg01) It gives me a summary table with lm for the first

Dear All, would you please provide your thoughts on the following: let us say I have: a <-c(1,5,8,15,32,69) b <-c(8.5,33) and I would like to extract from "a" the two values that are closest to the values in "b", where the length of this vectors may change but b will allways be shorter than "a". So at the end based on this example I should have the result

Dear R users, Does anyone knows how to run a glmm with one fixed factor and 2 random numeric variables (indices)? Is there any way to force in the model a separate interaction of those random variables with the fixed one? I hope you can help me. #eg. Reserve <- rep(c("In","Out"), 100) fReserve <- factor(Reserve) DivBoulders <- rep

Folks: Herein is a suggestion for a little R convenience function mainly to obtain unevaluated ... function arguments. It arose from a query on R-help on how to get these arguments. The standard (I think) idiom to do this is via match.call(expand.dots=FALSE)$... However, Bill Dunlap pointed out that this repeats the argument matching of the function call and suggested a couple of alternatives

I am new to R and have been doing my utmost to learn it in order to teach my students how to use it as an alternative to programs you have to purchase ­ and I am very grateful for the program and what it can doŠ.but I am having a slight problem as I also am not very much into programming ­ though willing to learn. I have been trying to apply a mixed model ANOVA to some data I have. In short ­ one

Hello, I am brand new in this site as well as in R. Please accept my early apology if it's not the right place to ask such a question. I have the following equation: b=[2(1-a)(1+2a)^0.5]/(1+3a) How can I solve the above equation for 'a' using R? Thanks in advance. KD [[alternative HTML version deleted]]

Dear all, I am a R beginner, and I am looking for a way to do the same thing for all levels of a column in a table. Basically, I have a bunch of protein sequences composed of different amino acid residues, and each residue is represented by an uppercase letter. I want to calculate the ratio of different amino acid residues at each position of the proteins. Here is an example table: Proteins

Hi everyone! I have some doubts about mixed effect models and I hope someone could help me. I´m trying to analyze a dataset coming from samples of dung beetles in the same forest fragments along 3 consecutive years (1994, 1995 and 1996) and 14 years after (2010). I sampled dung beetles in 18 different fragments with different sizes and different degrees of isolation. My aim is to determine

Hi all, I've fit a mixed linear model to some longitudinal data. I'm interested in the differences in patterns of decrease in the dependent variable according to group status, and my hypothesis particularly predicts a difference between the groups in trajectory of change at between specific ages. The data shows a significant interaction between group and the linear and quadratic effects

Dear all, I am trying to use R to fit mixed models. Take the following example, where ind is a random effect and sample is fixed. I wanted to fit Model 1: values = ind + sample Model 2: values =ind * sample Model 3: values=ind(sample) + sample Tried to use the below for mod1, but it did not work. Can anyone give some help on this. Thanks so much. mod1 <- lme(values ~ sample +

I have a data in the following form : CIN TRN_TYP 9079954 1 9079954 2 9079954 3 9079954 4 9079954 5 9079954 4 9079954 5 9079954 6 9079954 7 9079954 8 9079954 9 9079954 9 . . . . . . there are 100 types of CIN (9079954,12441087,15246633,...) and respective TRN_TYP first of all, I want this data to be

suppose I have two sets of vectors: x1,x2,...,xN and y1,y2,...,yN. I want N correlations: cor(x1,y1), cor(x2,y2), ..., cor(xN,yN). my sets of vectors are arranged as data frames x & y (vector=column): x <- data.frame(a=rnorm(10),b=rnorm(10),c=rnorm(10)) y <- data.frame(d=rnorm(10),e=rnorm(10),f=rnorm(10)) cor(x,y) returns a _matrix_ of all pairwise correlations: cor(x,y)

Hello all, I cannot seem to figure out this seemingly simple procedure. I want to sort a data frame by a specified character vector. So for : df.. <- data.frame(Season=rep(c("Summer","Fall","Winter","Spring"),4),Obs= runif(length(rep(c("Summer","Fall","Winter","Spring"),4)))) I want to sort the data frame

I have a stupid problem that is currently driving me crazy... Let us suppose that I want to draw a big red square in the middle of my current device (say X11) I tried the following code : pushViewport(viewport(xscale=c(0,1), yscale=c(0,1)), just=c("center", "center")) vp1 <- viewport(x=unit(0.5, "native"), y=unit(0.5, "native"), width=unit(0.4,

Hello, Does the (core) designation in the CRAN Task View indicate packages that provide basic/recommended functionality in that domain? I don't see it documented anywhere on the site. Thanks for your help.

Following the beginning tutorial, I typed help.start() and was given a choice of browsers. I picked chrome but got back that chrome is not found. I cannot seem to change or get rid of it now. I looked at /etc/R/Renviron but don't see anywhere to set browser (R_BROWSER = ${R_BROWSER ...etc) - nothing about chrome. I tried starting as "R_BROWSER= R" - same thing. How do I change the

Hi all, I am looking for a command for doing 2D filtering (rectangular or Gaussian) in R... I have looked at ksmooth, filter and convolve but they seem to be 1D... Any thoughts? Thanks a lot! [[alternative HTML version deleted]]

Hi, is there a way to replicate a data.frame like you can replicate the entries of a vector (with the repeat-function)? I want to do this: x <- data.frame(x, x) (where x is a data.frame). but n times. And it should be as cpu / memory efficient as possible, since n is pretty big in my case. thanks for any suggestions!