Lakens

library(MBESS)
library(pwr)

nSims <- 100000 #number of simulated experiments
p <-numeric(nSims) #set up empty container for all simulated p-values
obs_pwr <-numeric(nSims) #set up empty container
t <-numeric(nSims) #set up empty container
d_all<-numeric(nSims) 
N<-33 #number of participants

Lakens

library(metafor)

g <- escalc(
  measure = "SMD",
  n1i = 43, # sample size in group 1 is 50
  m1i = 1.3, # observed mean in group 1 is 5.6
  sd1i = 1, # observed standard deviation in group 1 is 1.2
  n2i = 43, # sample size in group 2 is 53
  m2i = 1, # observed mean in group 1 is 4.9
  sd2i = 1

Lakens

require(car) #Car package required for Levene's test

n1<-38 #size condition x
n2<-22 #size condition y
sd1<-1.11 #sd condition x
sd2<-1.84 #sd condition y 
m1<-0
m2<-0
trueD<-(m2-m1)/(sqrt((((n1 - 1)*((sd1^2))) + (n2 - 1)*((sd2^2)))/((n1+n2)-2)))
trueD

Lakens

# # # # # # # # # # #
#Initial settings----
# # # # # # # # # # #
if(!require(ggplot2)){install.packages('ggplot2')}
library(ggplot2)
if(!require(MBESS)){install.packages('MBESS')}
library(MBESS)
if(!require(pwr)){install.packages('pwr')}
library(pwr)
if(!require(meta)){install.packages('meta')}

Lakens

#Script based on Carter & McCullough (2014) doi: 10.3389/fpsyg.2014.00823

#Load Libraries
library(meta)
library(metafor)

#Insert effect sizes and sample sizes
es.d<-c(0.38,0.41,-0.14,0.63,0.22)
n1<-c(75,48,22,18,60)
n2<-c(75,52,21,20,55)

Lakens

library(segHT)
library(rpact)

looks <- 3
n_seg <- 50
alpha_level <- 0.05 
true_d <- 0.5 # can not enter 0, segmented_hyp_test_outcomes gives error

###############################
# Segmented procedure ----

Lakens

---
title: "Power Analysis for Interactions"
author: "Daniel Lakens"
date: "28-3-2020"
output:
  html_document: default
  pdf_document: default
  word_document: default
editor_options:
  chunk_output_type: console

Lakens

n<-2000 #total number of datapoints (per condition) you are willing to collect after initial 10

D<-0.0 #True effect size (Keep SD below to 1, otherwise, this is just mean dif, not d)
SD<-1 #Set True standard deviation.

p<-numeric(n) #store p-values
x<-numeric(n) #store x-values
y<-numeric(n) #store y-values

n<-n+10 #script calculates p-values after 10 people in each condition, so add 10 to number of datapoints

Lakens

# Scienceverse Sim

# install scienceverse
# devtools::install_github("scienceverse/scienceverse")

library(scienceverse)
library(faux)

set.seed(2) # set.seed(2) is a random draw where H1 is corroborated.

Lakens

# Scienceverse Sim

# install scienceverse
# devtools::install_github("scienceverse/scienceverse")

library(scienceverse)
library(faux)

set.seed(2) # set.seed(2) is a random draw where H1 is corroborated.