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.
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 libraryTo 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!
DeclareDesign, which will live as properly attributed entries in the library on our websiteThis project is generously supported by a grant from the Laura and John Arnold Foundation and seed funding from Evidence in Governance and Politics (EGAP).
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