A framework that brings together an abundance of common statistical models found across packages into a unified interface, and provides a common architecture for estimation and interpretation, as well as bridging functions to absorb increasingly more models into the collective library. Zelig allows each individual package, for each statistical model, to be accessed by a common uniformly structured call and set of arguments. Moreover, Zelig automates all the surrounding building blocks of a statistical work-flow--procedures and algorithms that may be essential to one user's application but which the original package developer did not use in their own research and might not themselves support. These include bootstrapping, jackknifing, and re-weighting of data. In particular, Zelig automatically generates predicted and simulated quantities of interest (such as relative risk ratios, average treatment effects, first differences and predicted and expected values) to interpret and visualize complex models.
|Author||Christine Choirat [aut], Christopher Gandrud [aut, cre], James Honaker [aut], Kosuke Imai [aut], Gary King [aut], Olivia Lau [aut], IQSS Harvard University [cph]|
|Date of publication||2017-06-07 22:43:55 UTC|
|Maintainer||Christopher Gandrud <email@example.com>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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