项目作者: nlsy-links

项目描述 :
Utilities and kinship information for behavior genetics and developmental research using the National Longitudinal Survey of Youth (NLSY)
高级语言: R
项目地址: git://github.com/nlsy-links/NlsyLinks.git
创建时间: 2013-01-13T16:05:33Z
项目社区:https://github.com/nlsy-links/NlsyLinks

开源协议:

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NlsyLinks

Project Status: Active – The project has reached a stable, usable
state and is being actively
developed.
R package
version
Package
downloads

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License

NlsyLinks is a free downloadable R package to facilitate Behavior
Genetic and Family Studies research using the NLSY samples (the National
Longitudinal Survey of Youth). These samples are based on a
cross-generational longitudinal nationally representative sample of over
30,000 participants followed for up to 35 years. There are almost 50,000
pairwise kinship links.

Get started at here the NLSY and
here for the NlsyLinks
package.

Installing

The release version of NlsyLinks can be installed from
CRAN.

  1. install.packages("NlsyLinks")

The latest development version of NlsyLinks can be installed from
GitHub after installing the
remotes package.

  1. install.packages("remotes")
  2. remotes::install_github(repo="nlsy-links/NlsyLinks")

There are roughly three versions of the links:

  1. The release versions are bundled in the NlsyLinks package and
    updated once or twice a year during development.
  2. The pre-release versions are downloadable from our team’s
    website
    and updated
    several times a month during development. Formats include R, SAS,
    and plain-text CSV.
  3. The development versions are downloadable from our determination
    repo

    updated several times a day during development.

Locations for Help and Development

This repository contains the code used in the
NlsyLinks R package. For
additional information about the package and using it in NLSY research,
please see https://nlsy-links.github.io/NlsyLinks.

This GitHub
repository

is our primary way of managing, tracking, and build-checking versions of
the source code. (We’re no longer using our R-Forge
site
.) The stable
releases (intended for most researchers) is available on the package’s
CRAN site.

We recently moved the forums to
https://groups.google.com/forum/#!forum/nlsy-links. Previous
conversations are available at our old
R-Forge and
Disqus sites.

Publication

Please see
research-publications
for a list of the 70+ publications arising from the kinship links. An
overview is available at:

Joseph Lee Rodgers, William H. Beasley, David E. Bard, Kelly M.
Meredith, Michael D. Hunter, Amber B. Johnson, Maury Buster, Chengchang
Li, Kim O. May, S. Mason Garrison, Warren B. Miller, Edwin van den Oord,
and David C. Rowe (2016). Behavior Genetics, 46.
https://doi.org/10.1007/s10519-016-9785-3.

The National Longitudinal Survey of Youth datasets (NLSY79;
NLSY-Children/Young Adults; NLSY97) have extensive family pedigree
information contained within them. These data sources are based on
probability sampling, a longitudinal design, and a cross-generational
and within-family data structure, with hundreds of phenotypes relevant
to behavior genetic (BG) researchers, as well as to other
developmental and family researchers. These datasets provide a unique
and powerful source of information for BG researchers. But much of the
information required for biometrical modeling has been hidden, and has
required substantial programming effort to uncover—until recently. Our
research team has spent over 20 years developing kinship links to
genetically inform biometrical modeling. In the most recent release of
kinship links from two of the NLSY datasets, the direct kinship
indicators included in the 2006 surveys allowed successful and
unambiguous linking of over 94 % of the potential pairs. In this
paper, we provide details for research teams interested in using the
NLSY data portfolio to conduct BG (and other family-oriented)
research.

Thanks to Funders

The current work on the NLSY Kinship links has been supported by NIH
Grant R01-HD065865 (Joe
Rodgers
,
PI).

Build Status and Package Characteristics

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