similar to: Boostrap p-value in regression [indirectly related to R]

Hello, I downloaded R today because I was told it has very good bootstrapping abilities. What I need to do is to program it (or use an existing program) to bootstrapping test for multimodality using nonparametric kernel density estimates as proposed by Efron and Tibshirani (1993). If anyone can get me started, I will be immensely grateful. Thanks. Sangeeta

Does R have a bootstrap command like SPlus, or do we have to form our own code if we want to do bootstrapping in R? Jason Parcon Western Michigan University e-mail addresses: s0parcon at wmich.edu parcon at stat.wmich.edu -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear R-help members, Apologies - I am posting on behalf of a colleague, who is a little puzzled as STATA and R seem to be yielding different survival estimates for the same dataset when treating a variable as ordinal. Ordered() is used to represent an ordinal variable) I understand that R's coxph (by default) uses the Efron approximation, whereas STATA uses (by default) the Breslow. but we

Hi Dr. Viechtbauer, I'm doing meta-analysis using your package 'metafor'. I used the 'IRFT' to transform the incident rate. But when I tried to back-transform the summary estimates from function rma, I don't know what's the appropriate ti to feed in function transf.iirft. I searched and found your post about using harmonic mean for ni to back-transform the double

I've put all ``current'' add-on packages into CRAN's source/contrib tree and created an INDEX file (attached below). As you can see, currently we have acepack bootstrap ctest date e1071 fracdiff gee jpn snns splines survival4 (Yes, e1071 and jpn are new ... more on the latter in a later mail.) In the near future, I am hoping for the following: oz (Bill

Hi All: I have to compute bootstrap confidence intervals, the statistic (incremental cost effectiveness ratio) is computed from two samples (intervention and control) of different sizes. All the bootstrap functions that I have seen use one dataset as argument. I may go ahead and get the desired number of bootstrap replications separately. I would appreciate if you could point me to a source of a

Dear R-Users, we are using a linux-cluster with RMPI and the snow package. We would like to do a double boostrap. We have a general function that implements the first boostrap (the outer) and we are wondering if we can include another bootstrap (the inner) in the same general function including another clusterApplyLB. For example: general function = function(...) { clusterApplyLB(cl,

Hi Does anyone know whether the rms package provides a confidence interval for the bootstrap-corrected Dxy or c-index? I have fitted a logistic model, and would like to obtain the 95% confidence interval of the bootstrap-corrected area under the ROC curve estimate. Thanks. [[alternative HTML version deleted]]

Hi, I am an astronomer and somewhat new to boostrap statistics. I understand the basic idea of bootstrap resampling, but am uncertain if it would be useful in my case or not. My problem consists of maximizing a likelihood function based on the velocities of a number of stars. My assumed distribution of velocities of these stars is:

Hi, Is there any working script, similar to deboostrap, for CentOS 5? I have found rpmstrap [1] at RPMforge.. but only works for CentOS-4, and appears that's out of date. thanks! [1] http://dag.wieers.com/rpm/packages/rpmstrap/ -- Santi Saez http://woop.es

Hello, I am performing a meta-analysis using the metafor package. My data are proportions and I used the Freeman Tukey double arcine (FT) transformation to fit the random effects model. Now I want to create a forest plot with my estimates backtransformed to the original scale of proportions. Can this be done? Regards, Patricia

Hello there I have the following model based on the hollings disc equation for the type II functional response for 2 data sets: nls(eaten~(a*suppl)/(1+a*h*suppl) where eaten is the number of prey eaten by a predator and suppl is the number of prey initially supplied to the same predator. I have parameter estimates of 'a' and 'h' for the two populations studied and would like

Hi, I have been looking for an R package which allowed to do meta-analysis (both pairwise and network/mixed-treatment) at arm-level rather than at trial-level, the latter being the common way in which meta-analysis is done. By arm-level meta-analysis I mean one that accounts for data provided at the level of the individual arms of each trial and that does not simply derive the difference between

This might be easy but I'm very new to R and this question doesn't seem to have any nice keywords that bring up relevant search results when I search the CRAN search engine. Therefore, I'll plead (as I have in the recent past) Newbie status. I have a data frame with two factors (Factor 1 and 2) which together specify another unique level. I want to create a third factor in the

Hi, I am new to R (I have most of my experience in SAS and SPSS). I was wondering if anyone has used both Resampling Stats and R, and could comment on strengths/relationships. Also, I have no clue on how to do the various examples from the book "Resampling: The New Statistics" in R. Can anyone give me some possible starting points? Or websites/books? Thanks, Brandon

Hello: I am trying to understand the method 'hatvalues(...)', which returns something similar to the diagonals of the plain vanilla hat matrix [X(X'X)^(-1)X'], but not quite.  A Fortran programmer I am not, but tracing through the code it looks like perhaps some sort of correction based on the notion of 'leave-one-out' variance is being applied. Whatever the

Hi, I have a little problem that puzzles me about contradictory results returned by a bootstraped t-test (as in MASS 3rd ed p. 146) versus a permutation t-test (as in MASS 3rd ed, p 147). Data are measurements done on 100 cells in 9 slides of fish blood. With one method, cells are randomly sampled, and with the other method, the operator selects cells arbitrarily (in a way it is done usually

Nelly Reduan a partag? un fichier OneDrive avec vous. Pour l?afficher, cliquez sur le lien ci-dessous. <https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb> [https://r1.res.office365.com/owa/prem/images/dc-png_20.png]<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb> Screenshot 2017-11-12 18.49.43.png<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb> Hello How can I perform

Dear Dushanthi, Please keep your e-mails on the R-Help list, where Michael has already given you some excellent advice. As Michael already explained, metafor can handle proportions, but does not have any specific functionality for categorical variables with more than 2 levels (at the moment). So, if it is logical and possible to do so, you could collapse the levels of the categorical outcome to 2

Hi all, I was conducting a meta-analysis of single proportions(i.e. without a control group) using the metafor package. When I performed a classic fail-safe N, I noticed that the result (the number of missing studies that would bring p-value to the alpha, to be exact)was different than that I got in Comprehensive Meta-Analysis Version 2.0. I wonder why R and CMA got different results. *Below is