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).