estimatr - Fast Estimators for Design-Based Inference
Fast procedures for a small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>. Fixed effects are absorbed by alternating projections rather than by dummy expansion, and Horvitz-Thompson variance is computed from the randomization declaration.
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cpp
14.17 score 135 stars 20 dependents 3.7k scripts 16k downloadsrandomizr - Easy-to-Use Tools for Common Forms of Random Assignment and Sampling
Generates random assignments for common experimental designs and random samples for common sampling designs.
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cpp
11.63 score 38 stars 17 dependents 611 scripts 6.6k downloadsDeclareDesign - Declare and Diagnose Research Designs
Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.
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designresearchsimulations
9.52 score 111 stars 2 dependents 614 scripts 2.7k downloadsri2 - Randomization Inference for Randomized Experiments
Randomization inference procedures for simple and complex randomized designs, including multi-armed trials, as described in Gerber and Green (2012, ISBN: 978-0393979954). Users formally describe their randomization procedure and test statistic. The randomization distribution of the test statistic under some null hypothesis is efficiently simulated.
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6.73 score 12 stars 178 scripts 334 downloadsvayr - Extensions for 'ggplot2' to Visualize as You Randomize
Extensions for 'ggplot2' that implement the "visualize as you randomize" principles of Coppock (2021) <doi:10.1017/9781108777919.022>, which can be especially useful when plotting experimental data. Provides position adjustments that arrange over-plotted points so that a statistical model can be shown in data-space, and a helper for graphing extreme value bounds when an experiment encounters attrition.
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5.80 score 7 stars 18 scripts 322 downloads