Re: [R] How to generate SE for the proportion value using a randomization process in R?

Dear Rui, I was wondering whether we have to square root of SD to find SE, right? bootprop <- function(data, index){ d <- data[index, ] sum(d[["BothTimes"]], na.rm = TRUE)/sum(d[["Time1"]], na.rm = TRUE) } R <- 1e3 set.seed(2020) b <- boot(daT, bootprop, R) b b$t0 # original sd(b$t) #

Re: [R] Plot histogram and lognormal fit on the same time

OK, but that's not the point of my comment. Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Fri, Jan 22, 2021 at 5:03 PM Abby Spurdle wrote: > Sorry, Bert. >

Re: [R] Plot histogram and lognormal fit on the same time

Sorry, Bert. The fitdistr function estimates parameters via maximum likelihood. (i.e. The "lognormal" part of this, is not a kernel). On Fri, Jan 22, 2021 at 5:14 AM Bert Gunter wrote: > > In future, you should try to search before posting. I realize that getting > good search terms can sometime

Re: [R] Help with Krippendorff's Alpha

Hi Jean, kripp.alpha expects a classifier by object (in your case, score) matrix as the first argument. If I read your code correctly you are getting the scores zigzagging across six columns when you want a 6 x 180 matrix. My guess is that you want: Trainers<-matrix(c(Trainer_1,Trainer_2, Trainer_

Re: [R] Help with Krippendorff's Alpha

Well, "Appreciate the help!" Indeed, you should for any that you receive. But do note per the posting guide linked below: "For questions about functions in standard packages distributed with R (see the FAQ Add-on packages in R

[R] Help with Krippendorff's Alpha

Hello! I am requesting help for a data set in which I have 6 evaluators (I've called them 'Trainers'), each of which took a questionnaire with 180 questions. The possible answers to the questions are ordinal numbers. I am looking to test inter-rater reliability of the questionnaire using Krippe

Re: [R] How to generate SE for the proportion value using a randomization process in R?

Hello, Something like this, using base package boot? library(boot) bootprop <- function(data, index){ d <- data[index, ] sum(d[["BothTimes"]], na.rm = TRUE)/sum(d[["Time1"]], na.rm = TRUE) } R <- 1e3 set.seed(2020) b <- boot(daT, bootprop, R) b b$t0 # original sd(b$t) # bootstrapped

[R] How to generate SE for the proportion value using a randomization process in R?

Hi All, I was trying to estimate standard error (SE) for the proportion value using some kind of randomization process (bootstrapping or jackknifing) in R, but I could not figure it out. Is there any way to generate SE for the proportion? The example of the data and the code I am using is attache

Re: [R] pgmm function errors in R

1. Please read the posting guide. Statistical questions and questions on non-standard (not shipped with standard R distro) packages are largely off topic here. 2. This CRAN task view might be of interest to you: https://cran.r-project.org/web/views/Econometrics.html 3. But as a general comment,

Re: [R] rmarkdown and source call to R file.

Thanks all of you for your answers. I managed to solve it after all. I was looking at the wrong place. It was an argument on the server.R. On Fri, 2021-01-22 at 09:17 -0600, Yihui Xie wrote: > I don't know the answer (there are multiple possible reasons for the > file not being found), but as the

[R] GAM

Hi, I’m currently using R studio to analyse data - I have 3 data sets consisting of months beginning in 02/2005-02/2020 with numbers of internet searches for 3 different countries. I have used a GAM to analyse this data and see if there are any significant differences or trends, but I am unsure

[R] pgmm function errors in R

Hello everyone, My name is Vadym, I am a last-year student at Stockholm School of Economics in Riga, currently working on my Bachelor's Thesis (so still learning R). For my research, I need a GMM estimator (preferable Arellano and Bond, 1991). I have been searching for a solution to my issue for ab

Re: [R] Why is rm(list=ls()) bad practice?

I think it's always difficult and sometimes impossible to take an existing session and convert it to the vanilla state, but it's very easy to run a new instance of R from an existing one. So instead of a clearws() function, I'd suggest a "runInVanilla" function, that takes some code as input,

Re: [R] Why is rm(list=ls()) bad practice?

Thanks Duncan for a clear argument about the "why". The suggestion of R --vanilla started a train of thought that one could do something like clearws <- function(){ # Try to clear workspace tmp <- readline("Are you sure you want to clear the workspace? ") print(tmp) if ( substr(toupper

Re: [R] rmarkdown and source call to R file.

I don't know the answer (there are multiple possible reasons for the file not being found), but as the first step to debug the problem, you may replace this chunk ```{r, echo=FALSE} library(knitr) source("helper.R", local = knitr::knit_global()) summarized_table<-give_table(params$ldf_sum

Re: [R] rmarkdown and source call to R file.

You would be better to try https://community.rstudio.com. Shiny is basically Tidyverse/Rstudio item and there will be a lot more expertise there. On Fri, 22 Jan 2021 at 02:02, Georgios via R-help wrote: > Hi! > I'm new in R and this list. > I made a shiny app using R studio. > my files are: >