random_missingness

A data.frame where missingness will be simulated.

aDataFrame

A string or a vector of strings that describe the column 
names (labels) where missingness will be simulated.

columnNames

The percentage of missingness within specified columns.
"Percent missing" uses a binomial distribution to simulate missing data.
Default is 10 (i.e. 10% missing). Use <code><a rd-options="" href="/link/impute_missingness?package=metagear&version=0.6" data-mini-rdoc="metagear::impute_missingness">impute_missingness</a></code> for
a summary of these randomly generated missing data.

percentMissing

Generates random <code>NA</code>'s in in a column or groups of columns of a data frame.
Used in imputation simulations based on complete datasets.

Functionalities for facilitating systematic reviews, data
extractions, and meta-analyses. It includes a GUI (graphical user interface)
to help screen the abstracts and titles of bibliographic data; tools to assign
screening effort across multiple collaborators/reviewers and to assess inter-
reviewer reliability; tools to help automate the download and retrieval of
journal PDF articles from online databases; figure and image extractions
from PDFs; web scraping of citations; automated and manual data extraction
from scatter-plot and bar-plot images; PRISMA (Preferred Reporting Items for
Systematic Reviews and Meta-Analyses) flow diagrams; simple imputation tools
to fill gaps in incomplete or missing study parameters; generation of random
effects sizes for Hedges' d, log response ratio, odds ratio, and correlation
coefficients for Monte Carlo experiments; covariance equations for modelling
dependencies among multiple effect sizes (e.g., effect sizes with a common
control); and finally summaries that replicate analyses and outputs from
widely used but no longer updated meta-analysis software (i.e., metawin).
Funding for this package was supported by National Science Foundation (NSF)
grants DBI-1262545 and DEB-1451031.

Marc J Lajeunesse

metagear

Comprehensive Research Synthesis Tools for Systematic Reviews
and Meta-Analysis

Marc J. Lajeunesse

random_missingness function

The percentage of missingness within specified columns.
"Percent missing" uses a binomial distribution to simulate missing data.
Default is 10 (i.e. 10% missing). Use <code><a rd-options='' href='impute_missingness'>impute_missingness</a></code> for
a summary of these randomly generated missing data.

random_missingness: Random generation of missingness in a data frame.

Description

Usage

Arguments

Value