richarddmorey

#### Solution

We first compute the two variances we need to compute the Bayesian ICC. Remember that we have two parameters that represent standard deviations, so we can use these to compute the variances.

```{r}
## Bayesian ICC
sigma2.eps = samples[,'sigma.eps']^2  
sigma2.alpha = samples[,'sigma.alpha']^2
```

richarddmorey

# These functions are a translation into R of Marden and 
# Perlman's (1982) FORTRAN code in Appendix A1 (p. 178). 
# Marden, J. I., & Perlman, M. D. (1982). THE MINIMAL COMPLETE CLASS OF 
# PROCEDURES FOR COMBINING INDEPENDENT NONCENTRAL F-TESTS. 
# In S. S. Gupta & J. O. Berger (Eds.), Statistical Decision Theory and 
# Related Topics III (pp. 139–181). Academic Press. 
# https://doi.org/10.1016/B978-0-12-307502-4.50014-3

rstar = function(nu, mu, eps = 5e-10, maxiter = 25){
  minrstar = max(.5, nu/(nu+mu))

richarddmorey

---
title: "Untitled"
format: 
  html:
    embed-resources: true
---

<script src="https://code.jquery.com/jquery-3.7.0.min.js"
			  integrity="sha256-2Pmvv0kuTBOenSvLm6bvfBSSHrUJ+3A7x6P5Ebd07/g="
			  crossorigin="anonymous"></script>

richarddmorey

/opt/homebrew/bin/pandoc +RTS -K512m -RTS index.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output index.html --lua-filter /Users/saprm3/Library/Caches/org.R-project.R/R/renv/library/flexTeaching3.api-91d1a6f0/R-4.2/aarch64-apple-darwin20/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /Users/saprm3/Library/Caches/org.R-project.R/R/renv/library/flexTeaching3.api-91d1a6f0/R-4.2/aarch64-apple-darwin20/rmarkdown/rmarkdown/lua/latex-div.lua --embed-resources --standalone --verbose --variable bs3=TRUE --section-divs --template /Users/saprm3/Library/Caches/org.R-project.R/R/renv/library/flexTeaching3.api-91d1a6f0/R-4.2/aarch64-apple-darwin20/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /var/folders/59/r7wjy0gn6yv59w19694x5gy80000gp/T//RtmpNWnHRc/rmarkdown-str16c6234aa443c.html 

richarddmorey

"score" "condition"
13 "control"
26 "control"
30 "control"
23 "control"
34 "control"
37 "control"
33 "control"
34 "control"
35 "control"

richarddmorey

library(dplyr)
library(memoise)

# Rolls
k = 3
# Sides
n = 5

sumDist = function(n,k,maxn = n){
  do.call(

richarddmorey

#' Create cover images for talks from a folder of PDFs
#' 
#' Requires imagemagick to be installed and in the path for the convert command
#' @param pdf_dir Directory containing PDF files of papers
#' @param img_dir Directory to output all the image files
#' @param crop_height How big to make the cropped images, relative to full page
#' @param fade_height How much of the image to fade to transparent at the bottom
#' @param density resolution for PNG images
#'
create_covers = function(pdf_dir, img_dir, crop_height = .5, fade_height = .25, density = 300){

richarddmorey

---
title: "Testing ricv"
author: "Richard D. Morey"
date: "3/25/2022"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
```

richarddmorey

library(dplyr)
library(ggplot2)

# Create data
tibble(
  g = rep(c('A','B'), each = 50),
  z = rnorm(length(g))
  ) |>
  group_by(g) |>
  mutate(

richarddmorey