search for: expts

...o the axes are scaled to accomodate all sets? Details: (Am I using R's data structures in a reasonable way?) I have many small datasets taken under different conditions, and have placed the vectors of x-values into one list, and y-values into another. The lists are part of a data frame: expts$x[[1]] is a vector of x-coordinates for experiment 1, expts$y[[3]] is a vector of y-coordinates for experiment 3, etc. I want to plot experiments 1, 4, and 7 together on a single plot, and have the axes automatically scaled. > plot(expts$x[[1]], expts$y[[1]]) > points(expts$x[[4]], expts$...

Hi, I'd like to normalize a dataset by dividing each row by the first row. Very simple, right? I tried this: > expt.fluor X1 X2 X3 1 124 120 134 2 165 163 174 3 52 51 43 4 179 171 166 5 239 238 235 >first.row <- expt.fluor[1,] > normed <- apply(expt.fluor, 1, function(r) {r / first.row}) >normed [[1]] X1 X2 X3 1 1 1 1 [[2]] X1 X2 X3 1

Hello All, I have a question regarding how glmmPQL should be specified. Which of these two is correct? summary(fm.3 <- glmmPQL(cbind(response, 100 - response) ~ expt, data = data.1, random = ~ 1 | subject, family = binomial)) summary(fm.4 <- glmmPQL(response ~ expt, data = data.2, random = ~ 1 | subject, family =

I have a data set with the following structure (with many more obs.): var1 expt day diameter 1 1 2 0.5 1 1 3 0.9 1 1 4 1.3 1 1 5 1.7 1 2 2 0.3 1 2 3 0.5 1 2 4 0.9 1 2 5 1.6 2 1 2 0.7 2 1 3 1.2 2 1 4 1.6 2 1 5 2.3 2 2 2 0.4 2 2 3 0.8 2 2 4 1.6 2 2 5 3.2 I can get separate regression analysis for each level of var1 and expt with the command: by(data3, data3$var1:data3$expt, function(x)

I am having what I think is a strange problem with applying TukeyHSD to an aov fit with error strata. TukeyHSD is supposed to take "A fitted model object, usually an 'aov' fit." aov (with error strata) is supposed to generate an object of type aovlist, which is a list of objects of type aov. But I can't seem to feed components of my aovlist to TukeyHSD. I guess I

Dear R-help I have two separate experiments, one a repeated-measures design, the other a split-plot. In a standard ANOVA I have usually undertaken a multiple-comparison test on a significant factor with e.g TukeyHSD, but as I understand it such a test is inappropriate for repeated measures or split-plot designs. Is it therefore sensible to use Helmert contrasts for either of these designs?

I am trying to do Tukey HSD comparisons on a repeated measures expt. I found the following example on r-help and quoted approvingly elsewhere. It is broken. Can anyone please tell me how to get it to work? I am using R 2.4.1. > require(MASS) ## for oats data set > require(nlme) ## for lme() > require(multcomp) ## for multiple comparison stuff > Aov.mod <- aov(Y ~ N + V +

I have written some programs in Common Lisp and I have been using SAS to pipe those programs to my lisp compiler in batch mode by using the %xlog and %xlst SAS commands. I wonder if there is in R a similar way to pipe commands to LISP so that all my work would be concentrated in R even when I have to call a LISP program? I have looked at the foreign library but this seems to adjust data types not

Hi, suppose I have data from 3 experiments which show conversion as a function of time for different boundary conditions, e.g. pressure, temperature. I want to plot all experiments as conversion over time grouped according to the temperature. However, since I have more than one experiment performed at the same temperature (but different pressures) I end up figuring out which curve belongs

Gday, This is a repost since I only had one direct reply and I remain mystified- This may be stupidity on my part but it may not be so simple. In brief, my problem is I'm not sure how to extract parameter values/effect sizes from a nonlinear regression model with a significant interaction term. My data sets are dose response curves (force and dose) for muscle that also have two

G'day, My problem is I'm not sure how to extract effect sizes from a nonlinear regression model with a significant interaction term. My data sets are multiple measurements of force response to an agonist with two superimposed treatments each having two levels. This is very similar to the Ludbrook example in Venables and Ripley. The experiment is that a muscle is exposed to an agonist

Hi All, I have a microarray dataset as follows:                           expt1 expt2 expt3  expt4 expt 5  gene1                val      val     val      val     val gene2                val      val     val      val    val . . .. gene15000       val       val     val      val     val The result is from the same organism in four different experiments.  Also, there are 4 replicates of each

Hi Ann Looks like a typo - I see "moreley.tab" that should be "morley.tab". Works for me after correcting that. > filepath <- system.file("data", "moreley.tab", package="datasets") > filepath [1] "" > > filepath <- system.file("data", "morley.tab", package="datasets") > filepath [1]

Hi all, I have 2 data frames the first contains a list with repeats of words and an associated response time (RT) measure for each word. The second is a tabulation of each unique word and other information such as the amount and of responses for each word. I need to determine the mean RT for each word and add that as a column in the second data frame. Any help would be appreciated Cheers

Hi, I'm using R-2.12 on a linux 64bit machine. When I run a chunk of code inside a foreach() %do% { ...} or %dopar% {...} (with doMC backend) I keep getting a segfault. Running the *same* code within lapply(something, function(x) ... ) doesn't result in any segfaults. I'll paste the output below, but I'm not sure it would be helpful. I'm more curious how to go about smoking

FYI, looks like support for Racoon is ending. Does anyone have any experience with the version in ipsec-tools ? ---Mike >Racoon users, > >This is the announcement that the kame project will quit providing >a key management daemon, the racoon, and that "ipsec-tools" will become >the formal team to release the racoon. >The final release of the racoon in the

Dear All I am trying to replicate a numerical application (not computed on R) from an article. Using, ks.test() I computed the exact D value shown in the article but the p-values I obtain are quite different from the one shown in the article. The tests are performed on a sample of 37 values (please see "[0] DATA" below) for truncated Exponential, Pareto and truncated LogNormal

Hello , I am not sure what the best solution is, but, in my hands using Org-mode version 8.3.2-elpa org-20150929 the reg-expt used to "cleanup extra prompts left in output" is over-aggressive and will trim session :output at lines consisting exclusively of blanks and periods such as produced when printing a BioConductor 'Views' object which wants to appear as #+RESULTS:

Hi, I am sorry to say, I do not know where the 'morley.dat' is that is mentioned as the sample data for the sample session on page 80 of Appendix A in the Introduction to R book. If you could get back to me soon about that would be great! Then I can prepare my next question, steve __________________________________________________ Do You Yahoo!? Send online invitations with Yahoo!

I would like to plot two different samples on the same scatterplot in R using different symbols for the different groups. Could someone please let me know how this can be done? Thank you very much. Thad ***************************************************************************** Thaddeus Tarpey Phone: (937) 775-2861 Wright State University