README.md
In sondreus/QuickCoefPlot: Quick and Easy Coefficient Plots with Options in R

QuickCoefPlot

Sondre U. Solstad

Easy Coefficient Plots with options in R

QuickCoefPlot is an easy interface for linear and glm coefficient plots in R. This includes the option to request robust, clustered, and bootstrapped standard errors, automatic labeling, and easy selection of coefficients to plot.

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/QuickCoefPlot")

library(QuickCoefPlot)

# Loading data
mydata <- readRDS("3d_example.RDS")

# Use the QuickCoefPlot to produce a regression table     
model <- lm(log_gdppc_mad ~  polity2 + tropical + desert + soil + near_coast + year, data = mydata)

QuickCoefPlot(model)

QuickCoefPlot(model, robust.se = FALSE)

QuickCoefPlot(model, boot.se = TRUE)

QuickCoefPlot(model, boot.se = TRUE, boot.b = 100, boot.plot.est = TRUE, legend.on = TRUE)

model - Fitted "lm" or "glm" object (e.g. lm(x ~ y, data = mydata)).
iv.vars.names - (Optional) Vector of desired independent variable names in plot output (e.g. c("GDP per capita", "Population")). Defaults to variables names if not provided.
plot.title (Optional) Specifies the title of the coefficient plot. Defaults to no title.
xlim (Optional) Vector of limits on x-axis of plot. If none supplied, this is automatically selected by ggplot.
**include.only (Optional) Vector of coefficients by number to keep in the plot (e.g. c(1, 2, 6)). If none specified, defaults to all.
robust.se (Optional) If TRUE, returns robust standard errors calculated using a sandwich estimator from the "sandwich" package. Defaults to TRUE (i.e. robust rather than normal standard errors).
cluster (Optional) Name of variable by which cluster-robust standard errors should be computed using the cluster.vcov command of the multiwayvcov package. If this variable is not in the model, a data frame common to both the model variables and the clustering variable must be supplied.
cluster.vars.names (Optional) Desired name or label of clustering variable to be reported in table output (e.g. "Country" yields a note on the bottom of the table reading "Country-Clustered Standard Errors in Parenthesis"). If cluster specified but no "cluster.vars.names" provided, "Cluster-Robust Standard Errors in Parenthesis" is reported.
boot.se (Optional) If TRUE, calculates bootstrapped confidence intervals. Defaults to FALSE.
boot.b (Optional) Integer specifying the number of bootstrap simulations to run. Defaults to 100.
boot.plot.est (Optional) If TRUE, plots the bootstrap estimates semi-transparently on the coefficient plot. Defaults to FALSE.
plot.lines (Optional) If FALSE, does not plot confidence intervals on the coefficient plot. Defaults to TRUE.
legend.on (Optional) If TRUE turns on the plot legend. Defaults to FALSE.
colors.off (Optional) If TRUE turns off default color scheme (sky-blue if p > 0.1, blue if p < 0.1, dark blue if p < 0.05, and black if p < 0.01)
plot.margin (Optional) Vector of plot margins in centimeters. Defaults to (1, 1, 1, 1).
text.size (Optional) Text size for plot elements.
hide.summary.lines (Optional) Vector of summary lines to hide in plot output. If none supplied, defaults to none.
add.summary.lines (Optional) Vector of summary lines to add to plot. If none supplied, defaults to none.
save.summary.df (Optional) Saves the coefficients and standard errors to a new data frame called "qcp.summary.df".
horserace (Optional) If TRUE produces a table comparing t-statistics instead of a coefficient plot.