similar to: Left censored responses in mixed effects models

Say I have a dataset that looks like Location Year GW_Elv MW01 1999 546.63 MW02 1999 474.21 MW03 1999 471.94 MW04 1999 466.80 MW01 2000 545.90 MW02 2000 546.10 The whole dataset is at http://doylesdartden.com/ExampleData.csv and I use the code below to do the graph but I want to do it without MW01. How can I

Hello, I am planning a study with the main point to evaluate the interaction of two treatments, but for ethical reasons one cell is empty, that with patients receaving no treatment at all Treatment B

Dear All, I got these results from the example in the function "dbeta": >x <- seq(0, 1, length=21) > dbeta(x, 1, 1) [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Any Idea? TIA Giovanni dr. Giovanni Parrinello Section of Medical Statistics Department of Biosciences University of Brescia 25127 Viale Europa, 11 Brescia Italy Tel: +390303717528 Fax: +390303701157

Sorry i had a misprint in the appendix code in the last email Hi I needed some help with ANOVA I have a problem with My ANOVA analysis. I have a dataset with a known ANOVA p-value, however I can not seem to re-create it in R. I have created a list (zzzanova) which contains 1)Intensity Values 2)Group Number (6 Different Groups) 3)Sample Number (54 different samples) this is created by the

Reading in the data from the file x <- read.csv( "ExampleData.csv", header = TRUE, stringsAsFactors = FALSE ) Subsetting as you want x <- x[ x$Location != "MW01", ] This selects all rows where the value in column 'Location' is not equal to "MW01". The comma after that ensures that all columns are copied into the amended data.frame. Rgds,

Hello everyone, I have a plot showing chloride concentrations for various point over time. I also have a dotted line that show the Secondary Maximum Contaminant Level (my screening limit) on the graphs at 250 mg/L. But I can not figure out how to include the dotted line / Secondary Maximum Contaminant Level in the legend. Any thoughts? My code is as following and is linked to my data on the

Hi Folks, I'm looking to do Confidence bands around LOESS smoothing curve. If found the older post about using the Standard error to approximate it https://stat.ethz.ch/pipermail/r-help/2008-August/170011.html Also found this one http://www.r-bloggers.com/sab-r-metrics-basics-of-loess-regression/ But they both seem to be approximations of confidence intervals and I was wonder if there was

Hi, I need to get mean and variance of right censored data. How can I do that? I have a vector of values (called a) and vector of booleans (whether value is censored) (called b). What to do with this? Sorry, I'm R beginner. Thank you! Pete

One set of data has censored (less-than detection limits) water chemistry concentrations for 80-100% of all observations. My initial trial-and-error attempts to apply the cenboxplot() method suggests that it has an upper limit to the percentage of censored observations. I do not see this limit in Dennis Helsel's second edition. Has anyone experience plotting censored data and can provide

Can survreg() handle interval-censored data like the documentation says? I ask because the command: survreg(Surv(start, stop, event) ~ 1, data = heart) fails with the error message Invalid survival type yet the documentation for Surv() states: "Presently, the only methods allowing interval censored data are the parametric models computed by 'survreg'"

Dear R users, I tried to analysis the hazard function of some data by coxph function in survival package. The type of the data include "left-censored", "right-censored", "both right-censored and left-censored" (btw, does this has a technical term?), and "complete" ones. I noticed that event (one parameter in "Surv()") might be an indicator for the

Dear list, I would like to plot the empirical cumulative distribution of the time needed by a treatment to attain a certain goal. A number of experiments is run with a strict time limit. In some experiments the goal is attained before the time limit, in other experiments time expires before the goal is attained. The situation is very similar to survivial analysis with censored data. I tryed

Hi, what is the best way to estimate a tobit(truncated) regression model in R ? Is there already a packet available ? Gruss Ralph Leonhardt -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body",

Dear all, Are there functions or packages in R that can handle interval-censored data? I have looked in various packages (such as survival5 or event), but it seems that only right-censored data can be analysed. More generally, are there methods to analyse both interval-censored observations and right-censored observations in the same data set? Thanks in advance. Emmanuel Paradis

I've submitted a message twice this evening and it has not appeared. Are messages censored on this board? regards john --------------------------------------------------------- John A Coll, Director, Connection Software 391 City Road, LONDON, EC1V 1NE, UK Tel: 020 7713 8000 From outside UK Tel: +44 20 7713 8000 Fax: 020 7713 8001 Fax: +44 20 7713 8001 Email:

Hi, I am wondering how to specify interval-censored data in coxph? The example in the help page summary(coxph(Surv(start, stop, event) ~ x, data = test2)) is for counting process data, is the counting process data the same as interval-censored data? Thanks __________________________________

Hello, ?can i implement this as 10% censored data where t gives me failure and x censored. Thank you p=2;b=120 n=50 set.seed(132); r<-sample(1:50,45) t<-rweibull(r,shape=p,scale=b) t set.seed(123);? cens <- sample(1:50, 5)? x<-runif(cens,shape=p,scale=b)? x Chris Guure Researcher, Institute for Mathematical Research UPM

dear R-users, I have to model counts where all counts above some threshold have been censored. In the same dataset I have too many zeroes for a Poisson or even a negative binomial distribution to make sense, so I would need a zero-inflated-censored negative binomial family for use in glmer (or glmmADMB?). That seems not to exist. my question is : how could I add a custom-built family of

I am a student (and very to new to R) working on a senior design project that is attempting to determine the demand distributions for single copy newspaper draws at individual sales outlet locations. Our sales data is right-censored, because sell-outs constitute a majority of the data, and we are also testing the relevance of including covariates (weather, seasonality, economic condition, etc.).

Dear R-helpers, excuse me if this is not exclusively an R-related question. I have data from a nested design, both temporally and spatially, and the reponse variable of interest is left-censored. That is, only values > "some treshold" are available, otherwise "LOW" is reported. Are there ways of building a linear model with both fixed and random effects, when the