similar to: Two-factor ANOVA Help

Dear R-ers, I am having trouble understanding why I am getting an error using glmmPQL (library MASS). I am getting the following error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 The long story: I have data from an experiment on pairwise comparisons between 3 treatments (a, b, c). So a typical run of an experiment

Hi All, Is there an easy way to reduce a data.frame to 1 'id' per row while keeping information from the other rows of that same variable, if applicable? e.g.: # data multi[1:15,] id r n wi wi.tau z k alliance a.rater eml treatment outcome o.rater german 1 100 0.2800000 44 41 21.72514 0.2876821 210 <NA> <NA> <NA> <NA>

Hi All. I need a bit of help extracting the residual error variance from the VarCorr structure from lmer. #Here's a 2-way random effects model lmer.1 <- lmer(rating ~ (1|person)+(1|rater), data = dat) #Get the structure vc.fit <- VarCorr(lmer.1) #results in..... $person 1 x 1 Matrix of class "dpoMatrix" (Intercept) (Intercept) 0.7755392 $rater 1 x 1 Matrix

Hi All, I am using fleiss kappa for inter rater agreement. Are there any know issues with Fleiss kappa calculation in R? Even when I supply mock data with total agreement among the raters I do not get a kappa value of 1. instead I am getting negative values. I am using the irr package version 0.70 Any help is much appreciated. Thanks and Regards M [[alternative HTML version deleted]]

Is there a function that calculates the inter-rater agreement index (kappa) in R? Thanks ../Murli [[alternative HTML version deleted]]

Hi All: Could anyone point me to a package that can calculate stratified kappa? My design is like this, 4 raters, 30 types of diagnosis scores, 20 patients. Each rater will rate each patient for each type of diagnosis score. The rater's value is nominal. I know I can measure the agreement between raters for each type of diagnosis score, e.g., calculate out 30 kappa values. My problem is I

Hi. I have data which i would want to assess the degree of agreement between two assays, e.g., to evaluate reproducibility or for inter-rater reliability. I have used the Pearson product-moment correlation coefficient. It looks good ranginging between 0.90 to 0.998. Though this looks good. I am told the Concordance correlation coefficient will give a better picture of how reproducible the assay

Can anybody, please, explain me how many parameter are estimated using randomLCA? For examples, model "dentistry.lca2random" estimate 1 scale (or variance, b_j) parameter and 2 position parameters (a_cj)? Doesn't it? Do I need at least 4 diagnostic tests for such a model? What happens if I specify options blocksize and byclass? How many diagnostic tests (or rater) I need?

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Greetings. I've been experimenting with some algorithms for document classification (specifically, a Naive Bayes classifier and a kNN classifier) and I would now like to calculate some inter-rater reliability scores. I have the data in a PostgreSQL database, such that for each document, each measure (there are 9) has three variables: ap_(measure), nb_(measure), and knn_(measure). ap is me

Hi all, I have an experiment where 5 raters assessed the quality of 24 web sites. (each rater rated each site once). I want to come up with a measure of reliability of the ratings for the web sites ie to what extent does each rater give the same (or similar) rating to each web site. My idea was to fit a random effects model using lme and from that, calculate the intraclass correlation as a

Hi everybody. I have a dilema and I think you guys can help me out. I am trying to shape the bandwith for about 500 clients, and I want the bandwith to be alocated dynamicly. Lets say I have 4 MB bandwith. I give each ip (500 IP''s) a sustained rate of 4 KB/sec . I wonder if I can shape the bandwith so when for example only 100 clients are online, to give them a rate of 4MB/100. How can

Hi JP, Wheezy currently has a 3.2 kernel -- does this still happen with this? If yes then I expect the xend.log (rater than the libvirt log) would be the place to look for clues. Ian.

Hello there, I would like to test the agreement amongst 6 raters for nominal data on a scale from 1-4, and conduct a latent class analysis in R. How should the data be formatted and what code should I use? Thank you very much Lisa Wang Princess Margaret Hospital Biostatistics tel:416 946 4501

Dear R users The following function is R code for the main compuations in the article: M. Eliasziw, S Lorraine Young, M Gail Woodbury and Karen Fryday-Field (1994): Statistical Methodology for the Concurrent Assessment of Intrarater and Intrarater Reliability: Using Goniometric Measurements as an Example. Physical Therapy 74 (8); 777-788 The function gives the estimated inter- and intrarater

Hi, I''m looking for a star rating component for RoR, a bit like Votio (http://redalt.com/downloads/ - find the votio heading) or the star rating used on Amazon. I don''t really need the AJAX capabilities, just the ability to bind the results to a hidden drop down, or radio inputs. Multiple raters per page is also an issue. Any recomendations? -- Posted via

Hi all! I am looking for some software that would work as a proxy between a SIP device (SIP phones and ATA boxes) and the Asterisk system running IAX. The reason is that I can only get IAX trow the firewalls, and can't change the settings. One solution I am using are getting several Asterisk system communicate trow IAX bout in this case would I rater have every persons computer act as a proxy

I am wondering if someone could cast some the box plot function. I have been having trouble manipulating boxplot to display the x & y axes in bold. I had the same problem with the x & y labels but managed to get around that with the "mtext" function. The below code is what I have thus far..... boxplot(SV ~ Rater, data=volumes, xlab=NA, ylab=NA, cex=0.75,

Please forgive me if someone has seen this duplicated email, because I sent the email to the wrong address just now. Hi, all, I'm estimating an inter-rater coefficient, Aickin (1990)'s alpha. It's been a long time for me to figure out how to make it work, but it's still of no avail. The problem seems to be my code with the optim() function. Can anyone help me take a look at the

Hello, I have 50 raters and 180 cases which are rated as malignant, probably malignant, probably benign, and benign. I want to compare all the raters but I want a weighted kappa to penalize differences between malignant and benign more than differences between malignant and probably malignant. I only found the weighted option in the 2-rater functions (kappa2, wkappa, cohen.kappa). The