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fabricatr (version 0.14.0)

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

1,576

Version

0.14.0

License

MIT + file LICENSE

Issues

10

Pull Requests

1

Stars

93

Forks

11

Maintainer

Graeme Blair

Last Published

February 9th, 2021

Functions in fabricatr (0.14.0)

draw_discrete

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

Expands data to a given length through recycling.
potential_outcomes

Build potential outcomes variables
get_unique_variables_by_level

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

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.
fabricatr

fabricatr package
draw_normal_icc

Draw normal data with fixed intra-cluster correlation.
fabricate

Fabricate data
reveal_outcomes

Reveal outcomes
split_quantile

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

Resample data, including hierarchical data
cross_levels

Creates panel or cross-classified data
correlate

Perform generation of a correlated random variable.
draw_binary_icc

Draw binary data with fixed intra-cluster correlation.
ALL

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

Draw multivariate random variables