Easy Effect Size Plots with options in R

options(width = 100)
library(stargazer)
library(zoo)
library(sandwich)
library(lmtest)
library(ggplot2)

QuickEffectSize is an easy interface for effect size plots in R. Using the Zelig package and ggplot2, it simulates and visualizes effect sizes of any zelig model: simply supply the model and the variable.

By default the plot shows 100 simulations for 100 values of the selected independent variable. These values are set to range from one standard deviation above to one standard deviation below the mean.

Written by Sondre U. Solstad, Princeton University (ssolstad@princeton.edu). Send me an email if you find this package useful or want to suggest an improvement or feature.

Installation instructions:

library(devtools)
install_github("sondreus/QuickEffectSize")

Example 1:

library(Zelig)
library(QuickEffectSize)

dat <- data.frame(y = rnorm(100), x1 = rnorm(100), x2 = rnorm(100))
dat$x3 <- dat$y + rnorm(100)
example.model <- zelig(y ~ x1 + x2 + x3, data = dat, model = "normal") 

qes(example.model, iv.var = "x3", xlab = "Using qes", ylab = "Productivity")

Example 2:

dat$y2 <- dat$y > 0.98
example.model <- zelig(y2 ~ x1 + x2 + x3, data = dat, model = "probit") 

qes(example.model, iv.var = "x3")

Arguments:

Citation:

Solstad, Sondre Ulvund (2019). QuickEffectSize: Quick Effect Size Plots in R. https://github.com/sondreus/QuickEffectSize#quickeffectsize

References:

Zelig: R Core Team. 2008. normal: Normal Regression for Continuous Dependent Variables in Christine Choirat, Christopher Gandrud, James Honaker, Kosuke Imai, Gary King, and Olivia Lau, "Zelig: Everyone's Statistical Software," http://zeligproject.org/

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.



sondreus/QuickEffectSize documentation built on April 26, 2022, 10:01 p.m.