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...erested 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 stat.math.ethz.ch > Subject: [R] Interrater and intrarater variability > (intraclass correlationcoefficients) > > Hello! > > I want to calculate the intra- and interrater reliability of > my study. The design is v...

Hallo! I read SPSS data in the following way: library(Hmisc) library(foreign) dat<-spss.get("surv_abb.sav") In R1.9.1 I got the message: "Error in all(arg == choices) : Object "typeDate" not found" In R1.8.0 the same script works fine. Does anybody know a possibilty to read a SPSS file under R1.9.1? Thanks! Karl

Hallo! I want to use the package bayesmix. Trying the examples I had no success. The reason is, I think: > haveJAGS() [1] FALSE Have read of JAGS executable (I could not find JAGS.exe in my R directory). What is JAGS? Where can I find or download it? Karl

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

Hallo! I want to plot multiple grouped data in a postscript file using a loop. As I use a loop no plot (or just one empty plot) is generated. Here an example: library(nlme) data(Loblolly) # example data from nlme postscript("PSFile.ps") for (i in 1:1) # just as example { plot(Loblolly) } dev.off() Result: Just an empty PSFile.ps. (Withoput the loop it works. May anybody help? Karl

Hello! I have the problem that in my function the passed variable is not used, but the variable name of the dataframe itself?- difficult to explain, but an easy example: TestFunc<-function(df, group) { ??? print(names(subset(df, select=group))) } df1<-data.frame(group="G1", visit="V1", value=0.9) TestFunc(df1, c("group", "visit")) Result: [1]

Hallo! GENERAL QUESTION: I'm trying to change the tick marks of the x-axis in a grouped data plot (nlme). CONCRETE EXAMPLE: In the example (see below) I want the x-axis to have tick marks at 0, 6, 12, 18, 24. How can I do this? WHAT I TRIED I tried "normal" methods like axis(...) but this does not work with this plot. And I also tried xlim=c(0,24) but the ticks are unchanged and

I came across a post by Karl Knoblick regarding the modeling of longitudinal data (see https://stat.ethz.ch/pipermail/r-help/2007-May/132137.html). I am often asked by physicians to perform what Karl refers to in his post as option 1: to perform paired t-tests against baseline at each follow up time point (30 days, 90 days, 6 months,...

...cribes six different ways to calculate ICCs from the same data set, all with different interpretations. All of the inputs for these calculations come from the repeated measures analysis which is described in P&B. Good luck! P. Message: 1 Date: Tue, 16 May 2006 10:09:54 +0000 (GMT) From: Karl Knoblick <karlknoblich at yahoo.de> Subject: [R] Interrater and intrarater variability (intraclass correlation coefficients) To: r-help at stat.math.ethz.ch Message-ID: <20060516100954.6267.qmail at web26504.mail.ukl.yahoo.com> Content-Type: text/plain; charset=us-ascii Hello! I want to calc...

Hallo! I have two groups (placebo/verum), every subject is measured at 5 times, the first time t0 is the baseline measurement, t1 to t4 are the measurements after applying the medication (placebo or verum). The question is, if there is a significant difference in the two groups and how large the differnce is (95% confidence intervals). Let me give sample data # Data

Hallo! I want to understand / recalculate what is done to get the CI of the logistic regression evaluated with lrm. As far as I came back, my problem is the variance-covariance matrix fit$var of the fit (fit<-lrm(...), fit$var). Here what I found and where I stucked: ----------------- library(Design) # data D<-c(rep("a", 20), rep("b", 20)) V<-0.25*(1:40) V[1]<-25

Dear R-Community! The example "oats" in MASS (2nd edition, 10.3, p.309) is calculated for aov and lme without interaction term and the results are the same. But I have problems to reproduce the example aov with interaction in MASS (10.2, p.301) with lme. Here the script: library(MASS) library(nlme) options(contrasts = c("contr.treatment", "contr.poly")) # aov: Y ~

Hallo! I have a problem with fitting data with nls. The first example with y1 (data frame df1) shows an error, the second works fine. Is there a possibility to get a fit (e.g. JMP can fit also data I can not manage to fit with R). Sometimes I also got an error singularity with starting parameters. # x-values x<-c(-1,5,8,11,13,15,16,17,18,19,21,22) # y1-values (first data set)

Hi! Is there a possibilty in R to carry out LOCF (Last Observation Carried Forward) analysis or to create a new data frame (array, matrix) with LOCF? Or some helpful functions, packages? Karl --------------------------------- Gesendet von http://mail.yahoo.de Schneller als Mail - der neue Yahoo! Messenger. [[alternative HTML version deleted]]

Hallo! I want to fit a function. The function is e.g.: y = c+m1*x if x<0, c+m2*x if x>=0 where m1, m2 and c is a parameter and x, y are variables of a data frame. I think using nls is appropriate. But I do not know, how to type this formula in nls. Can anybody help? (If there is a possibility to use a Heaviside-function this would be enough.) Karl

Hi Karl: a possible solution: require(foreign) mydata <- read.spss("somedata.sav", use.value.labels = TRUE, to.data.frame = TRUE) ----- for more information, try library(foreign) ?read.spss HTH, Arin Message: 21 Date: Mon, 26 Jul 2004 10:36:33 +0200 (CEST) From: Karl Knoblick <karlknoblich@yahoo.de> Subject: [R] Read SPSS data (*.sav) in R 1.8.0 (ok) and R1.9.1(error) To: r-help@stat.math.ethz.ch Message-ID: <20040726083633.90831.qmail@web52508.mail.yahoo.com> Content-Type: text/plain; charset=iso-8859-1 Hallo! <snipped....> Does anybody know a poss...

Hallo! Is there an error in cor to calculate Spearman correlation with cor if there are NA's? cor.test gives the correct result. At least there is a difference. Or am I doing something wrong??? Does anybody know something about this? a<-c(2,4,3,NA) b<-c(4,1,2,3) cor(a, b, method="spearman", use="complete.obs") # -0.9819805 cor.test(a, b,

Hallo! Does anybody know how to calculate a sample size estimation for proportions with continuity correction? ? I only found EpiR which seems to calculate without continuity correction: library(epiR) epi.studysize(treat = .65, control = .50, n = NA, sigma = NA, power = 0.80, r = 1, conf.level = 0.95, sided.test = 2, method = "cohort") $n [1] 340 Thanks! Karl

Hallo! Does anybody know a way to calculate the sample size for comparing AUC of ROC curves against 'by chance' with AUC=0.5 (and/or against anothe AUC)? Thanks! Karl

Hallo! Does anyone know a possibility to perform a sample size estimation for an ANCOVA? Would be great! Thanks Karl