similar to: How to extract ICC value from irr package?

Hello dear R help group. I encountered this old thread (http://tinyurl.com/dklgsk) containing the a similar question to the one I have, but left without an answer. I am and hoping one of you might help. A simplified situation: I have a factorial design (with 2^3 experiment combinations), for 167 subjects, each one has answered the same question twice (out of a bunch of "types" of

Hi, I am trying to install GenomeGraphs package from bioconductor, but failed by a non-zero exit error. From the error message, it seems that there is a shared library problem. Any suggestion on fixing it? Thanks so much. > sessionInfo() R version 2.10.1 (2009-12-14) x86_64-unknown-linux-gnu locale: [1] LC_CTYPE=en_US.iso885915 LC_NUMERIC=C [3] LC_TIME=en_US.iso885915

Hello! I want to calculate the intra- and interrater reliability of my study. The design is very simple, 5 raters rated a diagnostic score 3 times for 19 patients. Are there methods/funtions in R? I only found packages to calculate interrater variability and intraclass correlation coefficients for matrices of n*m (n subjects, m raters) - I have n subjects, m raters and r repetitions. Can

I am helping someone calculate ICC using R. I know R has several packages like irr, psy etc which provide options to calculate ICC (intraclass correlation coefficient). When getting ICC, we need to use the model: two-way mixed model with absolute agreement. I only found that in irr package, it provides the option of choosing one or two way and consistence or absolute agreement model. However,

It sounds as thought you are interested in Hoyt's Anova which is a form of generalizability theory. This is usually estimated using by getting the variance components from ANOVA. > -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Karl Knoblick > Sent: Tuesday, May 16, 2006 6:10 AM > To: r-help at

I'm using the lme function in nmle to estimate the variance components of a fully nested two-level model: Y_ijk = mu + a_i + b_j(i) + e_k(j(i)) lme computes estimates of the variances for a, b, and e, call them v_a, v_b, and v_e, and I can use the intervals function to get confidence intervals. My understanding is that these intervals are probably not that robust plus I need intervals on the

Hi, I'm trying to run a ICC calculation on a data frame. I get the following error message: Error in data.frame(x.s, subs = rep(paste("S", 1:n.obs, sep = ""), nj)) : arguments imply differing number of rows: 1700, 1750 I've looked at the data in the file and it seems to be okay. Any thoughts would be much appreciated. I'm getting used to R so if possible, I

I meet lots of problem when installing the package ROCR, do you have meet such problems? 1, biocLite("ROCR") 2, biocLite("gplots") 3, biocLite("Rgraphviz") 4, sudo apt-get install graphviz oh, no, unlimited question, what's wrong with R in ROCR or gplots or et al Error : object ‘nobs’ is not exported by 'namespace:gdata' installation of package

Dear All, Can I use lm() to fit more than one response in single expression. e.g data is a matrix of these variables R1 R2 R3 X1 X2 X3 1 2 1 1 2 3 Now i wnat to fit R1~X1 R2~X2 R3~X3 in turn, and I don't want to do it use loops of couse it it easy to make it using loops,but the proceed is very slow since the data is very big Can't anybody give me some tips or help, my eamil:

Karl, If you use one of the specialized packages to calculate your ICC, make sure that you know what you're getting. (I haven't checked the packages out myself, so I don't know either.) You might want to read David Futrell's article in the May 1995 issue of Quality Progress where he describes six different ways to calculate ICCs from the same data set, all with different

Hello R users: I am fairly new to R and am trying to figure out how to compute an intraclass correlation (ICC) and/or design effect for binary data? More specifically, I am trying to determine the amount of clustering in a data set - that is, whether certain treatment programs tend to work with more or less severe clients. The outcome variable is dichotomous (low severity / high severity)

Dear Profs. Ripley & Gamer, Thanks a lot for your prompt answer and your advice. Indeed, I managed to track the bug by launching R from the c-shell instead of the Mac GUI. In that case, after typing > library(irr) I obtained the following error message: > Erreur dans parse(file, n, text, prompt) : syntax error at > 653: irr.name =3D "R > Erreur : unable to load R code in

Hello, R-folks: Here is a statement I use to make a data frame: iccdata <- data.frame(i=rep(1:10,rep(2,10)),j=rep(1:2,10), x=c(0.35011,0.11989,0.13081,0.09919,0.16000,0.12000,0.00000,0.00000, 0.44023,0.32977,2.67081,2.63919,0.09050,0.03950,0.44019,0.30981,0.59000, 0.57000,4.03000,3.77000)) Then here are the data: > iccdata i j x 1 1 1 0.35011 2 1 2 0.11989 3 2 1 0.13081 4

I have a quick statistical question and hoped somebody has a tip for me without me having to go to the local statistician on Monday. I assess 4 statements from 90 subjects. Each of the 4 statements receives one of three responses (say -1, 0, or 1). I can use Cramer's V or Spearman correlations to assess the correlation between each pair of statements, but I am looking for a measure of

I've tried without success to calculate interaction and main effects contrasts using R. I've found the functions C(), contrasts(), se.contrasts() and fit.contrasts() in package gmodels. Given the url for a small dataset and the two-way anova model below, I'd like to reproduce the results from appended SAS code. Thanks. --Dale. ## the dataset (from Montgomery) twoway <-

Dear R users I would like to ask a question regarding to icc (intraclass correlation) or many biologists refer it to as repeatability. It is very useful to get icc for many reasons and it is easy to do so from linear mixed-effects models and many packages like psy, psychometric, aod and irr have functions to calculate icc. icc = between-group variance/(between-group variance + residual

The irr package seems to install correctly: > install.packages("irr") trying URL 'http://cran.us.r-project.org/src/contrib/irr_0.61.tar.gz' Content type 'application/x-tar' length 13848 bytes opened URL ================================================== downloaded 13Kb * Installing *source* package 'irr' ... ** R ** data ** help >>>

I am trying to replace a spreadsheet model of a project justification with an R script. I can't seem to track down R functions to calculate Internal Rate of Return and NPV? Am I missing something? NPV doesn't seem so difficult to calculate (at least for a regular series) but I am struggling to identify how to solve for IRR in R. It would be sufficient if it worked for a regular

Hi Cristian, I don't know about a R routine for exact CIs, but I found a function called "ageadjust" using a gamma distribution approximation some time ago -take a look at http://medepi.org/epitools/rfunctions/index.html. That Webpage seems a bit outdated now, but the calculations given in the ageadjust functions should still work, I think. Maybe this helps; regards Heinrich.

Hi, I'm essentially wanting to calculate intra- and inter-observer variabilities for the first principal component of an optic disc shape measure of a sample of individuals, so from what I can work out I need to work out an intraclass correlation coefficient(s). For the intra-data, I have 2 measurements taken on each individual by the same observer. For the inter-data, 2 observers have taken