similar to: concurve v 2.3.0 - Comparing Functions, Bootstrapping, and Exporting Tables

Could someone help me on how to correctly try to correct this error message arning : BCa Intervals used Extreme Quantiles Some BCa intervals may be unstable Warning message: Extreme Order Statistics used as Endpoints in: norm.inter(t, adj.alpha) Regards IF [[alternative HTML version deleted]]

HI everyone, I try to get some bootstrap CIs for coefficients obtained by quantile regression. I have influencial values and thus switched to quantreg.. The data is clustered and within clusters the variance of my DV = 0.. Is this sensible for the below data? And what about the warnings? Thanks in advance for any guidance, Kay > dput(d) structure(list(Porenfläche = c(4990L, 7002L, 7558L,

I like to bootstrap regression models, saving the entire set of bootstrapped regression coefficients for later use so that I can get confidence limits for a whole set of contrasts derived from the coefficients. I'm finding that ordinary bootstrap percentile confidence limits can provide poor coverage for odds ratios for binary logistic models with small N. So I'm exploring BCa confidence

Hello, I have a question regarding bootstrap confidence intervals. Suppose we have a data set consisting of single measurements, and that the measurements are independent but the distribution is unknown. If we want a confidence interval for the population mean, when should a bootstrap confidence interval be preferred over the elementary t interval? I was hoping the answer would be

hello, the following questions will without doubt reveal some fundamental ignorance, but hopefully you can still help me out. I'd like to bootstrap a coefficient gained on the basis of the coefficients in a logistic regression model (the mean differences in the predicted probabilities between two groups, where each predict() operation uses as the newdata-argument a dataframe of equal size as

Hello, I am having some trouble setting up a bootstrapping prodecure. I create artificial data and would like to use these to bootstrap a t-test statistic from these. Especially I do not really get how boot uses the indices variable or i variable. Can anybody help out? Thanks!! b0 <- 1/2 # intercept as given b1 <- 1 # slope as given n

Dear experienced R-users, I am having some probably trivial trouble estimating the confidence interval for the difference of two group means, with groups been of unequal sample size. I am using the "Bootstrap" package and the function "bcanon"(bcanon(x, nboot, theta, ...,alpha=c(0.025, 0.05, 0.1, 0.16, 0.84, 0.9, 0.95, 0.975)) for Nonparametric BCa confidence limits. The

In the boot package,consider a scalar function to boot. > estimator <- function(x, d) { + mean(x[d]) + } > > data <- city$u > b <- boot(data, estimator, R=1000) > b$t0 [1] 64 > ci <- boot.ci(b, type=c("bca"), conf=.95) > ci$bca conf [1,] 0.95 49.44 991.39 36.78807 110.0254 Now if I want estimators to return a vector,E.g. it's {c(mean(x[d]),

Sometimes one might like to obtain pointwise bootstrap bias-corrected, accelerated (BCA) confidence intervals for a large number of statistics computed from a single dataset. For instance, one might like to get (so as to plot graphically) bootstrap confidence bands for the fitted values in a regression model. (Example: Chiu S et al., Early Acceleration of Head Circumference in Children with

Dear R users, I am new to R. I would like to calculate bootstrap confidence intervals using the BCa method for a parameter of interest. My situation is this: I already have a set of 1000 bootstrap replicates created from my original data set. I have already calculated the statistic of interest for each bootstrap replicate, and have also calculated the mean for this statistic across all the

Dear all I am trying to compare the performances of several methods using the AUC0.1 and not the whole AUC. (meaning I wanted to compare to AUC's whose x axis only goes to 0.1 not 1) I came to know about the Mcneil Hanley test from Bernardo Rangel Tura and I referred to the original paper for the calculation of "r" which is an argument of the function cROC. I can only find the

Dear R-Experts, Thanks to Prof. Bonnett, I have got an R script working to calculate confidence intervals around the semipartial correlation coefficients. Now, I would like to calculate BCa bootstrap CIs using the boot library and the boot.ci(results, type="all") function. How could I modify my R script (here below reproducible example) to get the BCa bootstrap CIs ? CIsemipartcorr

Dear all, I try to compare the performances of several parameters to diagnose lameness in dogs. I have several ROC curves from the same dataset. I plotted the ROC curves and calculated AUC with the ROCR package. I would like to compare the AUC. I used the following program I found on R-help archives : From: Bernardo Rangel Tura Date: Thu 16 Dec 2004 - 07:30:37 EST

I might be missing something but I thought that AUC was a measure for comparing ROC curves, so there is nothing else needed to "compare" them. The larger AUC is the higher correlation of 2 variables compared. No other measures or calculations are needed. Jarek Tuszynski -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On

Please help. I found the code in the archive. The author of this script says: "The first function (seROC) calculate the standard error of ROC curve, the second function (cROC) compare ROC curves." Can some one explain to me what are the na, nn and r parameters which are used as the input to the following two functions? Thanks much in advance. > From: Bernardo Rangel Tura >

I have the following code:   ## to check correlation between the simulated uniform data x2 <- uni[,1] ; x2[1:10] y2 <- uni[,2] ; y2[1:10] result2 <- boot(cbind(x2,y2), f, 20) # get 95% confidence interval boot.ci(result2, type="bca") cor.test(x2,y2, method="pearson", conf.level=0.95)   part of my data:   > x2 <- uni[,1] ; x2[1:10]  [1] 0.63933145 0.71677785

I tried to reproduce a result from a former colleague which he got with S-plus bootstrap method. I don't have S-plus at hand. In R, there are 2 packages related to bootstrap method, bootstrap and boot. The former has a function called 'bootstrap' but this does not seem to conform either to the function used in S-plus nor to that described in MASS, 3d ed., p.144. The latter seems to be

I'm confused about name spaces. This morning I installed the boot package because I wanted to look at bca.ci. So I did library(boot), but then I had, > bca.ci Error: Object "bca.ci" not found I had a look in the boot R directory and bca.ci was there as expected. So then I took a look at the NAMESPACE file for the boot package and saw that bca.ci wasn't exported. I tried

>From: Jeff Cohen Date: Wed, 26 Jan 2005 19:47:44 -0800 > >Fixed. Yes, now it isn't the path. I've recorded this trace: ------------------------- llvm[3]: Building Debug Bytecode Archive libc.bca /bin/rm -f /C/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca /C/projects/build/MinGW/llvm-4-1/Debug/bin/llvm-ar rcsf /C/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca

On Thu, 2005-01-27 at 13:16, Henrik Bach wrote: > c:\projects\build\MinGW\llvm-4-1\Debug\bin\llvm-ar.exe: > c:/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca-000000: Can't destroy > file (hb:2): The process cannot access the file because it is being used by > another process. > make[3]: *** [/C/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca] Error 2 >