search for: expt

...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 1.330645 1.358333 1.298507 [...

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 = binomial)) One might think it makes no difference, but it does. I have a...

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,...

...le to use the error strata, but I did expect to be able to use the final stratum. I have posted a complete example, which I hope explains why I am confused, below. Any help will be appreciated. Jonathan Dushoff ---------------------------------------------------------------------- > morley$Expt = factor(morley$Expt) > morley$Run = factor(morley$Run) > > mod = aov(Speed~Expt+Run, data=morley) > class(mod) [1] "aov" "lm" > > TukeyHSD(mod)$Expt diff lwr upr 2-1 -53.0 -117.91627 11.916268 3-1 -64.0 -128.91627 0.916268 4-1 -88.5 -15...

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.mo...

...e. Thanks DATA _NULL_; FILE 'c:\cl.lisp' LRECL=1024; PUT "(defun run (num Mn SD)"; PUT "(setq mix (list nil))"; PUT "(dotimes (n num)"; PUT "(setq u (- (* 2 (random 1.0)) 1)"; PUT "v (- (* 2 (random 1.0)) 1)"; PUT "w (+ (expt u 2) (expt v 2)))"; PUT "(when (< w 1)"; PUT "(progn"; PUT "(setq z (sqrt (/ (* -2 (log w)) w))"; PUT "x (* u z)"; PUT "y (* v z)"; PUT "mix (append (list x) mix)"; PUT "mix (appen...

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

...treatment A to change upper and ed50. We want to know if treatment B blocks the effect of treatment A and if so to what degree. This is similar to the Ludbrook example in Venables and Ripley, however they only had one treatment and I have two. my approach The dataframe is structured like this: expt treatA treatB dose force. 1 - - 0.1 20 1 - - 0.2 40 ... 4 + + 0.1 20 4 + I used a groupedData object: mydata=groupedData(force ~ dose | expt) I used an nlme obect to model the data as follows (pseudocode): myfit.nlme <- nlme(force ~ ss_tpl(dose, upper, ed50,slope), fixed=list(e...

...ook) . This is done for each combination of two factors (treatmentA and Treatment B) each having two levels (- and +). Each set of measurements is obtained on a muscle from a different animal (i.e. each dose response curve represents an independent experiment). The data are stored as follows: expt treatA treatB dose force I use a groupedData object mydata=groupedData(force ~ dose | expt) I used an nlme obect to model the data as follows (pseudocode): myfit <- nlme(force ~ ssThreeParLogistic(dose, upper, ed50,slope), fixed=list(ed50~factor(treatmentA)*factor(treatmentC))) The ThreePa...

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...

...uot;datasets") > filepath [1] "" > > filepath <- system.file("data", "morley.tab", package="datasets") > filepath [1] "C:/PROGRA~1/R/R-30~1.1/library/datasets/data/morley.tab" > mm <- read.table(filepath) > head(mm) Expt Run Speed 001 1 1 850 002 1 2 740 003 1 3 900 004 1 4 1070 005 1 5 930 006 1 6 850 > Steven McKinney Statistician Molecular Oncology and Breast Cancer Program British Columbia Cancer Research Centre > -----Original Message----- > From: r-si...

...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 Lee Data frame 1 > head(alldat) s expt session cycle trial left.right freq concr word rt resp Response correct corrResp 121 1a a 1 C1 1 1 lf hc pianist 1529 old hi FALSE new 122 1a a 1 C1 2 1 hf hc sweat 1518 new hi TRUE new 123 1a a...

..., expr))}) 10: doSEQ(obj, substitute(ex), parent.frame()) 11: foreach(chr = chrs, .packages = "GenomicFeaturesX", .verbose = TRUE) %do% { .gc <- duplicate(gcache, pre.load = NULL) on.exit(dispose(.gc)) cat("===", chr, "===\n") \ apaSummary(expt, .gc, chr, pvd.policy, utr.index, polya.variants, gene.collapse) } 12: apaSummaryCrank(bpm[[1]], gcr, chrs[21:22], gene.collapse = "longest") Possible actions: 1: abort (with core dump, if enabled) 2: normal R exit 3: exit R without saving workspace 4: exit R saving workspace...

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

...lues are above 30 ############### 39.7 582 439.9 47.1 83.9 41.2 893.1 192 106.2 216.7 1243.4 52.8 351.6 36.2 431.5 57.3 1602.1 822.2 260.1 58.7 6299.9 814.9 137.2 203.8 1263.5 53.7 1313 118.4 167.8 70.1 503.7 64.8 529.9 87.8 2465.4 317.9 2753.9 ############### # [1] FUNCTIONS ############### #EXP exptfit_function(x,b, plot.it = F, lty = 1){ if (mode(x) != "numeric") stop("need numeric data") x <- x[!is.na(x)] x <- sort(x) lambda <- length(x)/sum(x-b) if(plot.it) { lines(x, dexpt(x, lambda = lambda, b...

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: #+begin_example Views on a 230...

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