R Packages

For two decades, IQSS has led the development of Open Source analytical tools for researchers. Many of these tools take the form of R packages - modules that provide specialized functionality for the R programming language. These packages are freely available for anyone to use, modify, and contribute to.

Now IQSS invites researchers to showcase their own work by having us custom build your R package. IQSS empowers researchers to disseminate their work, and others to replicate it, by providing an Analytical Tool Building service that will develop a state-of-the-art R package from your raw code. Through this R package, your new statistical method, analysis pipeline, or vizualization can directly impact the people in your research group, your academic field, and the broader scholarly community.

IQSS affiliates have played a leading role in the development of the following R packages:

Example image for {clarify}

{clarify} uses simulation to make interpretable inferences about any quantity of interest from a wide variety of statistical models. 

Learn more about clarify

Example image for {MatchIt}

{MatchIt} implements matching methods for improving parametric statistical models for estimating treatment effects in observational studies and reducing model dependence.

Learn more about MatchIt

{MatchingFrontier} example image

{MatchingFrontier} provides tools to manage the bias-variance trade-off when matching in observational studies.

Learn more about MatchingFrontier

Example image for {cem}

{cem} implements a method for improving causal inferences called "Coarsened Exact Matching".

Learn more about cem

Example image for {Amelia}

{Amelia} is a tool that "multiply imputes" missing data in a single cross-section, from a time series, or from a time-series-cross-sectional data set.

Learn more about Amelia

Example image for {WhatIf}

{WhatIf} offers easy-to-apply methods to evaluate counterfactuals that do not require sensitivity testing over specified classes of models.

Learn more about WhatIf

Example image for {Readme2}

{Readme2} implements methods for estimating category proportions in an unlabeled set of documents given a labeled set.

Learn more about Readme2

Example image for {ei}

{ei} implements methods described in Gary King's (1997) book: A Solution to the Ecological Inference Problem.

Learn more about ei

Example image for {lmw}

{lmw} computes the implied weights of linear regression models for estimating average causal effects and provides diagnostics based on these weights.

Learn more about {lmw}

Example image for {EvoPhylo}

{EvoPhylo} performs morphological character partitioning and analyzes outputs from clock Bayesian inference for phylogenetic analyses. 

Learn more about EvoPhylo

{netlit} logo

{netlit} provides functions to generate network statistics from a literature review.

Learn more about netlit

Example image for {Morphoscape}

{Morphoscape} constructs, analyzes, and visualizes spatially organized trait data into adaptive landscapes.

Learn more about Morphoscape