The metadat package contains a large collection of meta-analysis datasets. These datasets are useful for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.
The current official (i.e., CRAN) release can be installed within R with:
The development version of the package can be installed with:
This builds the package from source based on the current version on GitHub.
A listing of all datasets in the package can be obtained with help(package=metadat). Each dataset is also tagged with one or multiple concept terms. These concept terms refer to various aspects of a dataset, such as the field/topic of research, the outcome measure used for the analysis, the model(s) used for analyzing the data, and the methods/concepts that can be illustrated with the dataset. The datsearch() function can be used to search among the existing datasets in the package based on their concept terms or based on a full-text search of their corresponding help files.
You can also read the documentation online at https://wviechtb.github.io/metadat/ (where the output from the example analyses corresponding to each dataset is provided).
We welcome contributions of new datasets to the package. For each dataset, there must be a citable reference, ideally in a peer-reviewed journal or publication. The general workflow for contributing a new dataset is as follows:
metadat package in R in the usual manner (i.e., install.packages("metadat")).data-raw directory. The file should be named dat.<author><year>.<ext>, where <author> is the last name of the first author of the publication from which the data come, <year> is the publication year, and <ext> is the file extension (e.g., .txt, .csv).data-raw directory named dat.<author><year>.r that reads in the data, possibly does some data cleaning/processing, and then saves the dataset to the data directory (using save()), with name dat.<author><year>.rda.metadat package (i.e., library(metadat)), and then run the prep_dat() function (either set the working directory to the location of the source package beforehand or use the pkgdir argument of the prep_dat() function to specify the source package location).man directory, named dat.<author><year>.Rd. Edit the help file, adding the title and a short description of the dataset in general, a description of each variable in the dataset, further details on the dataset (e.g., the field of research, how the data was collected, the purpose of the dataset or what it was used for, the effect size or outcome measure used in the analysis, the types of analyses/models that can be illustrated with the dataset), a reference for the source of the dataset, one or multiple concept terms, the name and email address of the contributor of the dataset, and (optionally) example code to illustrate the analysis of the dataset.dat.<author><year>.<ext>, dat.<author><year>.r, dat.<author><year>.rda, and dat.<author><year>.Rd files and open up a new issue at GitHub, attaching the zip file..txt or .csv format, along with a meta-data file (format doesn’t matter) that includes the information described above.If you use these data, please cite both the metadat package (see citation("metadat") for the reference) and the original source of the data as given under the help file of a dataset.
If you think you have found an error in an existing dataset or a bug in the package in general, please go to https://github.com/wviechtb/metadat/issues and open up a new issue.