DesignLibrary provides simple interface to build designs using the package DeclareDesign. In one line of code users can specify the parameters of individual designs and diagnose their properties. The designers can also be used to compare performance of a given design across a range of combinations of parameters, such as effect size, sample size, assignment probabilities and more.


Designs

Design

Vignette

Designer

Design Inspector

Block Cluster Two Arm Design

Cluster Sampling Design

Factorial Design

Mediation Analysis Design

Multi Arm Design

Pretest Posttest Design

Randomized Response Design

Regression Discontinuity Design

Spillover Design

Two Arm Design

Two By Two Design

Two Arm Attrition Design

Process Tracing Design

Binary IV Design

Two Arm Covariate Design

My Design

Installing the design library

To install the latest stable release of DesignLibrary, please ensure that you are running version 3.4 or later of R and run the following code:

install.packages("DesignLibrary")

If you would like to use the latest development release of DesignLibrary, please ensure that you are running version 3.4 or later of R and run the following code:

devtools::install_github("DeclareDesign/DesignLibrary", keep_source = TRUE)

Contributing designs and designers

We welcome contributions to the library!


This project is generously supported by a grant from the Laura and John Arnold Foundation and seed funding from Evidence in Governance and Politics (EGAP).