similar to: epi.2by2

Hi all, I want to know how to perform the test Breslow-Day test for homogeneity of odds ratios (OR) stratified for svytable. This test is obtained with the following code: epi.2by2 (dat = daty, method = "case.control" conf.level = 0.95, units = 100, homogeneity = "breslow.day", verbose = TRUE) where "daty" is the object type table svytable consider it, but

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

Hello, I was wondering who to contact to see about somehow interconnecting or integrating the programs R and Epi Info. I have been involved in the development of Epi Info which is a software program developed by the Centers for Disease Control and Prevention (CDC) in Atlanta (www.cdc.gov/epiinfo<http://www.cdc.gov/epiinfo>). Epi Info allows for creating data entry systems and performs

The name conflicts in Epi and ROC packages (2 'ROC' functions are the problem) cause the following code to work once, but not twice: library(MASS); data(cats); x = cats[,2] y = ifelse(cats[,1]=='F',0,1) library(Epi); ROC(x,y,grid=0)$AUC library(ROC); AUC(rocdemo.sca(y, x, dxrule.sca)) What is the standard way of resolving name conflicts? Ask maintainers to resolve

Hello: Does anybody knows if Epi Info, from CDC (www.cdc.gov/epiinfo) runs on Wine? I did try AppDB first but there are no entries for Epi Info. Epi Info is a data base for epidemiology and public-heath developed by Centers for Disease Control and Prevention (USA) and heavilly used in the world. It is based on Access 97 or 2000 witch I found in Frank's Corner AppDB. Thank you, Gerson

Dear all, I would like to calculate the optimal cut off (threshold) of a test using the Epi package. Here I am presenting some data based on the output of two tests. I am interested in identifying the optimal cut off an its 95% CI. Running the ROC() function with the Epi package I obtain a nice picture that returns what I interpret as the optimal cut off with lr.eta=0.431. would be this the

There is now an Epi-package on CRAN. It is intended for epidemiological analysis in R. It has its own homepage, http://www.pubhealth.ku.dk/~bxc/Epi The package has been used at the course "Statistical practise in Epidemiology with R", see http://www.pubhealth.ku.dk/~bxc/SPE. A mailing list for people using R for epidemiology, R-sig-Epi, has been set up, see

Dear all, I would like to calculate the optimal cut off (threshold) of a test using the Epi package. Here I am presenting some data based on the output of two tests. I am interested in identifying the optimal cut off and its 95% CI. Running the ROC() function with the Epi package I obtain a nice picture that returns what I interpret as the optimal cut off with lr.eta=0.491. would be this the

There is now an Epi-package on CRAN. It is intended for epidemiological analysis in R. It has its own homepage, http://www.pubhealth.ku.dk/~bxc/Epi The package has been used at the course "Statistical practise in Epidemiology with R", see http://www.pubhealth.ku.dk/~bxc/SPE. A mailing list for people using R for epidemiology, R-sig-Epi, has been set up, see

The stat.table function in the Epi package won't do standard deviations. It didn't seem that it would be difficult to add an "sd" function to the stat.table function. Following the example for the mean, I set up a similar function for the sd (and included it as an options) but it just won't work. (I tried sending messages to the Epi mailing list after subscribing but my mail

Hi all, I have a question and I do not know If I am at the right place to ask this question. But is there someone that has the formula of CKD-Epi in code in R? I have tried a lot of loops, but none of the approaches give me the right answer. Is there someone who has this formula coded? Thank you! [[alternative HTML version deleted]]

A new major upgrade of the Epi package for Epidemiological data analysis has been put on CRAN, it is now at version 1.0.7. It contains an entirely new way of representing follow-up data on multiple timescales and multiple states. See the function Lexis(). Plus a lot of other useful stuff for epidemiological analysis. See more on the package homepage, www.biostat.ku.dk/~bxc/Epi Note also that

Hi, I have a dataset (see attached) with 2 variables "Y" is binary, "x" is a continuous variable. I want to calculate area under the curve (AUC) for the ROC curve, but I got different AUC values using ROC() from Epi package vs. rcorr.cens() from rms package: test<-read.table("test.txt",sep='\t',header=T,row.names=NULL) y<-test$y x<-test$x

R Fans-- I am having problems with the following code. It worked under R 2.6.0 but not in 2.7.0. > library(Epi) > df <- read.table( "c:/Documents and Settings/Troy S/My Documents/debug_chisq_080613b.txt") > summary(df) cvd agecat Min. :0.0000 (0,40] :1 1st Qu.:0.0000 (40,60]:2 Median :0.0000 Mean :0.3333 3rd

Hi Sjoerd, > Trying to remember how everything fits together here, but could > get.active.lane.mask not create the %mask of the VP intrinsics? Or in other > words, in the vectoriser, who's producing the %mask and %evl that is > consumed by the VP intrinsics? > > I'm not sure what would be the best way here. I think about the Loop Vectorizer. I imagine at some point we

Greetings! I suspect that there is an error in the code for the function ci.pd() in the Epi package. This function is for computing confidence intervals for a difference of proportions between two independent groups of 0/1 responses, and implements the Newcombe ("Nc") method and the Agrasti-Caffo "AC" method. I think there is an error in the computation for the Newcombe

Hello Simon, Thanks for your replies, very useful. And yes, thanks for the example and making the target differences clear: ; Some examples: ; RISC-V V & VE(*): ; %mask = (splat i1 1) ; %evl = min(256, %n - %i) ; MVE/SVE : ; %mask = get.active.lane.mask(%i, %n) ; %evl = call @llvm.vscale() ; AVX: ; %mask = icmp (%i + (seq <8 x i32> 0,1,2,.,)), %n, ; %evl

Hi everyone, I emailed yesterday thinking I had a problem with reading matrix information as numerical output into epiR. After working on the data frame today, I realise it's a problem with the data itself rather than the syntax. An original data frame of min max T1 1.500000e+01 3.999954e+01 SE1 0.000000e+00 1.000000e+00 PRE

; RISC-V V & VE(*): ; %mask = get.active.lane.mask(%i, %i) ; %evl = min(256, %n - %i) ; MVE/SVE/AVX : ; %mask = get.active.lane.mask(%i, %n) ; %evl = call @llvm.vscale() For VE, we want to do as much predication as possible through %evl and as little as possible with %mask. This has performance implications on VE and RISC-V - VE does not generate a mask from %evl but %evl is

Hi all, On 11/5/20 10:32 AM, Roger Ferrer Ibáñez wrote: Hi Sjoerd, thanks for pointing us to this intrinsic. I see it returns a mask/predicate type. My understanding is that VPred intrinsics have both a vector length operand and a mask operand. It looks to me that a "popcount" of get.active.lane.mask would correspond to the vector length operand. Then additional "control