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IalsaSynthesis

An R package for synthesizing information across collaborating research.

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IALSA (Integrative Analysis of Longitudinal Studies of Aging) research network unites approximately 100 longtidinal studies from all over the world. IALSA makes primary use of a coordinated analysis approach and various harmonization methods. Our projects involve dealing with multiple longitudinal studies, each of which may count numerous statistical models, making the synthesis of results particularly arduous. The IalsaSynthesis package offers software tools for extracting, pooling, evaluating, and reporting the results of a large number of statistical models. See out flagship project, stemming from coordinated analysis workshop in Portland in February of 2015.

Package Crew

Will Beasley (University of Oklahoma Health Sciences Center, Department of Pediatrics, Biomedical & Behavioral Research Core), and

Andrey Koval (University of Victoria, Department of Psychology).

Download and Installation Instructions

The development version of IalsaSynthesis can be installed from GitHub after installing the devtools package. (The release version will be available on CRAN closer to the Cambridge conference in July 2015.)

install.packages("devtools") #If it's not already installed.
devtools::install_github(repo="IALSA/IalsaSynthesis")

The package documentation for the development version on GitHub can be viewed without installing the package.

Collaborative Development

Consistent with IALSA goals, we encourage input and collaboration from the overall community. If you're familar with GitHub and R packages, feel free to submit a pull request. If you'd like to report a bug or make a suggestion, please create a GitHub issue; issues are a usually a good place to ask public questions too. However, feel free to email Andrey or Will privately (andkov@uvic.ca or wibeasley@hotmail.com).

Thanks to Funders

IALSA is funded through an NIH/NIA Program Project Grant (P01AG043362; 2013-2018) to Oregon Health & Science University (Program Directors: Scott Hofer, Andrea Piccinin, Jeffrey Kaye, and Diana Kuh) and previously funded by NIH/NIA (R01AG026453; 2007-2013) and CIHR (103284; 2010-2013).

Code coverage over time: codecov.io