Learn R Programming

DesignLibrary (version 0.1.10)

Library of Research Designs

Description

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.

Copy Link

Version

Install

install.packages('DesignLibrary')

Monthly Downloads

672

Version

0.1.10

License

MIT + file LICENSE

Issues

24

Pull Requests

2

Stars

30

Forks

3

Maintainer

Jasper Cooper

Last Published

October 18th, 2021

Functions in DesignLibrary (0.1.10)

assignment_string

Generates string of assignment of value to argument
match.call.defaults

Argument matching with defaults
binary_iv_designer

Create a binary instrumental variables design
factorial_designer

Create a factorial design
cluster_sampling_designer

Create a design for cluster random sampling
DesignLibrary

DesignLibrary: A package for creating designs
get_design_code

Get the code from a design
block_cluster_two_arm_designer

Create a two-arm design with blocks and clusters
construct_design_code

Generates clean code string that reproduces design
code_fixer

Substitute approach
mediation_analysis_designer

Create a design for mediation analysis
sub_expr_text

Substitute text from expressions in design code
str_within

Takes substring between matched strings. Avoids dependency on stringr package.
return_args

Generates character string for non-fixed arguments in a designer using substitution approach.
two_arm_designer

Create a one-level two-arm design
spillover_designer

Create a design with spillovers
two_by_two_designer

Create a two-by-two factorial design
process_tracing_designer

Create a process-tracing design
pretest_posttest_designer

Create a pretest-posttest design
randomized_response_designer

Create a randomized response design
two_arm_attrition_designer

Create design with risk of attrition or post treatment conditioning
regression_discontinuity_designer

Create a regression discontinuity design
two_arm_covariate_designer

Create a simple two arm design with a possibly prognostic covariate
multi_arm_designer

Create a design with multiple experimental arms