search for: uncensoring

Does anyone know of an R package that I can use to uncensor a normal or log-normal dataset? I'm particularly interested in the MLE method of Cohen (1959), "Simplified estimators for the normal distribution when samples are single censored or truncated," Technometrics, 1(3), 217-237. Of course, if there is anything better, I'd be glad to hear about that too. Thanks. Rick

Dear R users, This is a basic question. I want to fit a Weibull distribution. fitdistr(data, "weibull") works and it is a maximum likelihood fitting. Is it a good method ? Or is it better to write a function for the log-likelihood and the gradient and to use a numerical routine ? Fitdistr works for uncensored data, but what can I use for censored (and uncensored) data ? Thank you

Since I read the list in digest form (and was out ill yesterday) I'm late to the discussion. There are 3 steps for predicting survival, using a Cox model: 1. Fit the data fit <- coxph(Surv(time, status) ~ age + ph.ecog, data=lung) The biggest question to answer here is what covariates you wish to base the prediction on. There is the usual tradeoff between too few (leave out something

I get to 53 percent of files copied and I get the message that c:\lotuscomponent/lttsn32.dll is in use by another application and terminates install. Help me? BTW I get a message about contacting Microsoft support about mytab11.c. Well this is a Microsoft clean installation. Took me hours to the point where the installer will load and run. -----= Posted via Newsfeeds.Com, Uncensored Usenet

Hi , I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide

Hello, I have setup mod_ntlm_winbind to provide authentication for an Apache 1.3.33 webserver running on Fedora Core 3. The authentication works, but I have run into a problem when using Internet Explorer. It seems that the problem might be with Internet Explorer itself, but here is what I think is happening - the browser will not submit any forms with a POST method on a website protected with

I have water chemistry data with censored values (i.e., those less than reporting levels) in a data frame with a narrow (i.e., database table) format. The structure is: $ site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1 1 1 1 1 1 1 ... $ sampdate: Date, format: "2007-12-12" "2007-12-12" ... $ preeq0 : logi TRUE TRUE TRUE TRUE TRUE

I read through Harrington and Fleming (1982) but it is beyond my statistical comprehension. I have survival data for insects that have a very finite expiration date. I'm trying to test for differences in survival distributions between different groups. I understand that the medical field is most often dealing with censored data and that survival analysis, at least in the package survival,

Dear R-listers, I am an MD and clinical epidemiologist developing a measure of comorbidity severity for patients with liver disease. Having developed my comorbidity score as the linear predictor from a Cox regression model I want to compare the discriminative ability of my comorbidity measure with the "old" comorbidity measure, Charlson's Comorbidity Index. I have nearly 10,000

I am reposting my message from April 8th because I never received a response to the original post: Dear R-listers, I am an MD and clinical epidemiologist developing a measure of comorbidity severity for patients with liver disease. Having developed my comorbidity score as the linear predictor from a Cox regression model I want to compare the discriminative ability of my comorbidity measure with

I have two alternative Cox models with C-statistics 0.72 and 0.78. My question is if 0.78 is significantly greater than 0.72. I'm using rcorrp.cens. I cannot find the U statistics in the output of the function. This is the output of the help example: > x1 <- rnorm(400) > x2 <- x1 + rnorm(400) > d.time <- rexp(400) + (x1 - min(x1)) > cens <- runif(400,.5,2) > death

Dear R users: I'm generating the following survival data: set.seed(123) n=200 #sample size x=rbinom(n,size=1,prob=.5) #binomial treatment v=rgamma(n,shape=1,scale=1) #gamma frailty w=rweibull(n,shape=1,scale=1) #Weibull deviates b=-log(2) #treatment's slope t=exp( -x*b -log(v) + log(w) ) #failure times c=rep(1,n) #uncensored indicator id=seq(1:n) #individual frailty indicator

I'm using RH 7.1 with 20011108. Wine is running well with the few simple apps that I use with it. The only problem that I'm having is with printing. I've followed the somewhat conflicting instructions that I've found around the web to use the internal PS driver and at least gotten that much to show up in the dialog box on WinSpice3. However, when I attempt to print I get

Hi, I'm trying to calculate 95% confidence interval of C statistic of logistic regression model using rcorr.cens in rms package. I wrote a brief function for this purpose as the followings; CstatisticCI <- function(x) # x is object of rcorr.cens. { se <- x["S.D."]/sqrt(x["n"]) Low95 <- x["C Index"] - 1.96*se Upper95 <- x["C

Hi, I am trying to get the maximum likelihood estimator for lognormal distribution with censored data;when we have left, interval and right censord. I built my code in R, by writing the deriving of log likelihood function and using newton raphson method but my estimators were too high " overestimation", where the values exceed the 1000 in some runing of my code. is there any one can

Dear R-help, This is an example in the {Hmisc} manual under rcorr.cens function: > set.seed(1) > x <- round(rnorm(200)) > y <- rnorm(200) > round(rcorr.cens(x, y, outx=F),4) C Index Dxy S.D. n missing uncensored Relevant Pairs Concordant Uncertain 0.4831 -0.0338 0.0462 200.0000

I've successfully reformatted data frames from long to wide with reshape2, but this time I'm getting errors that I want to understand and resolve. Here's the data frame structure and the results of the melt() and dcast() functions: str(waterchem) 'data.frame': 128412 obs. of 8 variables: $ site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1

First of all congratulations on reaching alpha status. I was wondering if you people are implementing multiple layer support into the codec. I don't know if it should be in the container (ogg) or codec (theora) but perhaps the syncing requires at least support in the codec. For example a commercial: a cup of hot chocolate with steam escaping. Little action, low bandwidth. Then comes the

Hi folks; This may not even be Samba related, but I'm stumped, so I thought I'd toss this one out here. All the client machines are on 192.168.1.x, all netmasks are configured as /24, etc. I cannot browse the network. I CAN connect to a resource on the server just fine if I specify the full name, but an attempt to bring up the network browser shows the network name (DENNINGER) but

lrm does some binning to make the calculations faster. The exact calculation is obtained by running f <- lrm(...) rcorr.cens(predict(f), DA), which results in: C Index Dxy S.D. n missing 0.96814404 0.93628809 0.03808336 32.00000000 0.00000000 uncensored Relevant Pairs Concordant Uncertain 32.00000000