knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The goal of researchfunctions is to allow me to keep all my functions for my project in one place.
You can install the development version from GitHub with:
# install.packages("devtools") devtools::install_github("dakthomps00/researchfunctions")
This is a basic example which shows you how to solve a common problem:
Say we want to get confidence intervals of effect sizes for random normally distributed data sets we would do this
library(researchfunctions) cohen <- replicate(10000, cohensd_OG(75,0,1,1)) mad <- replicate(10000, deltamad_OG(75,0,1,1)) confidint(cohen, 75) confidint(mad,75)
This is another basic example which shows you how to solve a common problem:
Say we want to get confidence intervals of effect sizes for random normally distributed data sets that are contaminated with another normally distributed data set, we would do this
library(researchfunctions) cohen <- replicate(10000, cohensd_A(75,0.8,0.2,0,1,1.5,1,1,0.5)) mad <- replicate(10000, deltamad_A(75,0.8,0.2,0,1,1.5,1,1,0.5)) cohen1 <- t(cohen) mad1 <- t(mad) confidint(cohen1[,1], 75) confidint(mad1[,1],75)
This is another basic example which shows you how to solve a common problem:
Say we want to get confidence intervals of effect sizes for random normally distributed data sets that are contaminated with a uniform data set, we would do this
library(researchfunctions) cohen <- replicate(10000, cohensd_B(75,0.8,0.2,0,1,1.5,1,1,2)) mad <- replicate(10000, deltamad_B(75,0.8,0.2,0,1,1.5,1,1,2)) cohen1 <- t(cohen) mad1 <- t(mad) confidint(cohen1[,1], 75) confidint(mad1[,1],75)
This is another basic example which shows you how to solve a common problem:
Say we want to find effect sizes for 2 Poisson distributions
before <- rpois(75,2) after <- rpois(75,3) cohensdcalc(before,after) deltamadcalc(75,before,after)
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