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fabricatr (version 0.16.0)

Imagine Your Data Before You Collect It

Description

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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Install

install.packages('fabricatr')

Monthly Downloads

1,592

Version

0.16.0

License

MIT + file LICENSE

Issues

10

Pull Requests

1

Stars

93

Forks

11

Maintainer

Graeme Blair

Last Published

February 11th, 2022

Functions in fabricatr (0.16.0)

correlate

Perform generation of a correlated random variable.
reveal_outcomes

Reveal outcomes
ALL

Magic number constant to allow users to specify ALL for passthrough resampling
fabricate

Fabricate data
fabricatr

fabricatr package
get_unique_variables_by_level

Find which variables are unique at a given level in hierarchical data
join_using

Helper function handling specification of which variables to join a cross-classified data on, and what kind of correlation structure needed. Correlation structures can only be provided if the underlying call is a link_levels() call.
potential_outcomes

Build potential outcomes variables
cross_levels

Creates panel or cross-classified data
draw_binary_icc

Draw binary data with fixed intra-cluster correlation.
split_quantile

Split data into quantile buckets (e.g. terciles, quartiles, quantiles, deciles).
draw_normal_icc

Draw normal data with fixed intra-cluster correlation.
draw_multivariate

Draw multivariate random variables
draw_discrete

Draw discrete variables including binary, binomial count, poisson count, ordered, and categorical
draw_likert

Recode a latent variable into a Likert response variable
resample_data

Resample data, including hierarchical data
recycle

Expands data to a given length through recycling.