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 href="/link/impute_missingness?package=metagear&version=0.1" rd-options="" data-mini-rdoc="metagear::impute_missingness">impute_missingness</a></code> 

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; automated data extractions from scatter-plots; 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effect sizes with a common control); and finally summaries that replicate analyses and outputs from widely used but no longer updated meta-analysis software.  Funding for this package was supported by National Science Foundation (NSF) grants DBI-1262545 and DEB-1451031.

random_missingness: Random generation of missingness in a data frame.

Description

Usage

Arguments

Value