metaDAT: metaDAT: Tools for data management, reshaping and basic...
In trinker/metaDAT: Tools for Data Management in Meta-Analysis
Description
metaDAT is intended to provide a frame work for meta
analysis that uses a list structure rather than the
traditional dataframe data storage. In a meta-analysis
with correlated/dependent data each study may have
several effect sizes. This causes the problem of more
effect sizes than moderators resulting in the need to
replicate these variables in multiple rows. This
approach utilize JabRef (a refrence management tool) as
the input program and R as the import system. This
approach means less repetition of moderator variables in
the data frame and allows for importing a correlation
matrix rather than a vector of correlations through a
list approach rather than the traditional dataframe.
This will lead to more efficient analysis, less error in
input and more coherant structure to the data.
Details
It is intednded that all data is input directly into
JabRef through a user defined entry. JabRef can be
obtained from http://jabref.sourceforge.net/. After
JabRef has been installed a custom entry type must be
created as described in this link:
http://jabref.sourceforge.net/help/CustomEntriesHelp.php.
The custom entry can be named whatever the user desires
but the default read in of the read.MD function is meta,
thus it is advisable to follow this convention. The
variables for the meta-analysis are entered in as custom
fields. These will be the variables stored within the
list structure (MDlist) in the metaDAT package.
After the data has been entered metaDAT provides a numer
of functions to prepare the data into a structure for
analysis provided my any of the excellent meta analysis
packages available as an add on package.
trinker/metaDAT documentation built on May 31, 2019, 8:52 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
metaDAT is intended to provide a frame work for meta analysis that uses a list structure rather than the traditional dataframe data storage. In a meta-analysis with correlated/dependent data each study may have several effect sizes. This causes the problem of more effect sizes than moderators resulting in the need to replicate these variables in multiple rows. This approach utilize JabRef (a refrence management tool) as the input program and R as the import system. This approach means less repetition of moderator variables in the data frame and allows for importing a correlation matrix rather than a vector of correlations through a list approach rather than the traditional dataframe. This will lead to more efficient analysis, less error in input and more coherant structure to the data.
Details
It is intednded that all data is input directly into JabRef through a user defined entry. JabRef can be obtained from http://jabref.sourceforge.net/. After JabRef has been installed a custom entry type must be created as described in this link: http://jabref.sourceforge.net/help/CustomEntriesHelp.php. The custom entry can be named whatever the user desires but the default read in of the read.MD function is meta, thus it is advisable to follow this convention. The variables for the meta-analysis are entered in as custom fields. These will be the variables stored within the list structure (MDlist) in the metaDAT package.
After the data has been entered metaDAT provides a numer of functions to prepare the data into a structure for analysis provided my any of the excellent meta analysis packages available as an add on package.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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