richarddmorey

x = rlogis(10000,0,10)

mod = "model{
y ~ dlogis(0, 1/10)
}
"
library(rjags)
m = rjags::jags.model(file = textConnection(mod))
s = rjags::coda.samples(m,n.iter = 10000,variable.names = "y")

richarddmorey

library(tictoc)
df = data.frame(y = rnorm(10000000), x = rbinom(10000000,1,.5))

tic()
z = df[df$x == 1,]$y
toc()

rm(z)

tic()

richarddmorey

N = c(16, 16)
y = c(3, 9)
actual_result = prop.test(y, N, correct = FALSE)


compute_p_value = function(p0){
  ## Probability of all outcomes,
  ## assuming independence
  pr_X2s = 
    outer( dbinom(0:N[1], N[1], p0), 

richarddmorey

data(attitude)

library(cocor)
## EQtest at alpha = .05 needs a 90% CI
cocor(~ rating + complaints | rating + learning, data = attitude, alternative = "less", 
      null.value = .2, test = "zou2007", conf.level = .9)

zou_ci_func = function(conf.level, ...)
{

richarddmorey

## Get file off OSF
tf = tempfile(fileext = ".xlsx")
download.file(url = "https://osf.io/846cb/download", destfile = tf)

## Create summaries
library(tidyverse)

readxl::read_xlsx(tf) %>%
  group_by(STN_NUMBER, DIRECTION) %>%
  summarise(

richarddmorey

---
title: "Power and precision"
author: "Richard D. Morey"
date: "11/06/2020"
output: 
  html_document:
    dev: png
    self_contained: no
editor_options: 
  chunk_output_type: console

richarddmorey

---
title             : "The title"
shorttitle        : "Title"

author: 
  - name          : "First Author"
    affiliation   : "1"
    corresponding : yes    # Define only one corresponding author
    address       : "Postal address"
    email         : "my@email.com"

richarddmorey

desired_precision = .6

N1 = 5
N2 = 6

# Function to compute CDFs of "precisions" (CI widths)
SS_func = function(W, n, alpha = .05){
  n * (n - 1) * W^2 / (4 * qt(1-alpha/2, n - 1)^2)
}

richarddmorey

# Prior setup
prior_concentration = 10
# null 
p0 = c(0.3, 0.3, 0.4)


# fake data, null

richarddmorey