estimatr - Fast Estimators for Design-Based Inference

Fast procedures for 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>.

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cpp

11.69 score 135 stars 15 dependents 2.4k scripts 16k downloads

randomizr - 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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10.45 score 37 stars 15 dependents 496 scripts 8.6k downloads

fabricatr - Imagine Your Data Before You Collect It

Helps you imagine your data before you collect it. Hierarchical data structures and correlated data can be easily simulated, either from random number generators or by resampling from existing data sources. This package is faster with 'data.table' and 'mvnfast' installed.

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8.96 score 91 stars 7 dependents 294 scripts 4.7k downloads

DeclareDesign - 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

8.53 score 108 stars 1 dependents 496 scripts 3.9k downloads

DesignLibrary - Library of Research Designs

A 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, and assignment probabilities.

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6.87 score 30 stars 144 scripts 3.9k downloads