Lakens

#Standardized p-value
#This is untested alpha software provided with no guarantees - use at your own risk

#Good 1982: P SQRT(N/100)
#Enter the observed p-value and the sample size

p_stan <- function(p, N){
  p * sqrt(N/100)
}

Lakens

#Load packages
library(readxl)
library(mailR)

#Read student data
info <- read_excel("student_names_email.xls",
                   sheet = 1,
                   col_names = TRUE)

#Loop from 1 to the number of email addresses in the spreadsheet

Lakens

options(scipen=999) #disable scientific notation for numbers

#Figure 1 & 2 (set to N <- 5000 for Figure 2)
# Set x-axis upper and lower scalepoint (to do: automate)
low_x<--1
high_x<-1
y_max<-2

#Set sample size per group and effect size d (assumes equal sample sizes per group)
N<-50 #sample size per group for indepndent t-test

Lakens

Lakens

#Make sure JAGS is installed or R will crash: https://sourceforge.net/projects/mcmc-jags/files/JAGS/4.x/
require(BEST) #To calculate HDI
require(TOSTER) #To calculate Equivalence Tests

set.seed(1)

x<-rnorm(100) #Generate 100 random normally distributed observations
y<-rnorm(100) #Generate 100 random normally distributed observations

#ROPE test

Lakens

# Code from https://osf.io/aqi5j/ made by original authors, adapted by Daniel Lakens
# Download the csv file from https://osf.io/aqi5j/
# Paper: http://www.tandfonline.com/doi/full/10.1080/23743603.2016.1273647

require(car)

# IMPORTANT: change this to match your path/file
fileLocation <- 'C:\\Users\\Daniel\\surfdrive\\Data\\blog volunteer study\\VolunteeringDataFile_05.09.16.csv'

# Dienes functions

Lakens

#Create single plot for graph----
power <- seq(0.01,1,0.01)
alpha <- seq(0.01,1,0.01)
pH0 <- 0.5
tp<-((1-pH0)*power)
fp<-((pH0)*alpha)
likelihood_ratio<-outer(tp, fp, "/")

#Create color shading
nrz<-nrow (likelihood_ratio)

Lakens

if(!require(ggplot2)){install.packages('ggplot2')}
library(ggplot2)
if(!require(Rcpp)){install.packages('Rcpp')}
library(Rcpp)
if(!require(MASS)){install.packages('MASS')}
library(MASS)
options(digits=10,scipen=999)


#Set color palette

Lakens

if(!require(BayesFactor)){install.packages('BayesFactor')}
library(BayesFactor)
#to get emoticons for each test, set wait to 0.5 and showfaces to 1. 
#When running large number of simulations, set wait to 0 and showfaces to 0.
options(scipen=20) #disable scientific notation for numbers
waitx<-0.5 #To see a small wait between individual trials, set a wait time to e.g., 0.5 
showfaces<-1 #Set to 0 if you do not want the faces, set to 1 if you want to see the faces

cohensd<-0.3 #set true effect size
n<-75 #sample size in each group

Lakens

if(!require(ggplot2)){install.packages('ggplot2')}
library(ggplot2)
if(!require(pwr)){install.packages('pwr')}
library(pwr)

nSims <- 100000 #number of simulated experiments

M<-106 #Mean IQ score in the sample
n<-26 #set sample size
SD<-15 #SD of the simulated data