NlsyLinks (version 1.003)

Links79Pair: Kinship linking file for pairs of relatives in the NLSY79 and NLSY79 Children and Young Adults

Description

This dataset specifies the relatedness coefficient (ie, 'R') between subjects in the same extended family. Each row represents a unique relationship pair. An extended family with $k$ subjects will have $k$($k$-1)/2 rows. Typically, Subject1 is older while Subject2 is younger. The dataset *eventually will* contain Gen1 and Gen2 subjects. "Gen1" refers to subjects in the original NLSY79 sample (http://www.bls.gov/nls/nlsy79.htm). "Gen2" subjects are the biological children of the Gen1 females -ie, those in the NLSY79 Children and Young Adults sample (http://www.bls.gov/nls/nlsy79ch.htm). Currently this dataset contains only Gen2 siblings. However, it soon will be generalized to the five categories specified by the RelationshipPath variable. Code written using this dataset should NOT assume it contains only Gen2 sibiling pairs. See below for an example of filtering the relationship category.

Usage

data(Links79Pair)

source

Gen1 information comes from the May 15, 2010 release of the http://www.bls.gov/nls/nlsy79.htm{NLSY79 sample}. Gen2 information comes from the Sept 15, 2010 release of the http://www.bls.gov/nls/nlsy79ch.htm{NLSY79 Children and Young Adults sample}. Data were extracted with the NLS Investigator (https://www.nlsinfo.org/investigator/). The internal version for the links is Links2011V28.

Details

Subjects will be in the same extended family if either: [1] they are Gen1 housemates, [2] they are Gen2 siblings, [3] they are Gen2 cousins (ie, they have mothers who are Gen1 sisters in the NLSY79, [4] they are mother and child (in Gen1 and Gen2, respectively), or [5] they are {aunt|uncle} and {niece|nephew} (in Gen1 and Gen2, respectively). The variables Subject1Tag and Subject2Tag uniquely identify subjects. For Gen2 subjects, the SubjectTag is identical to their CID (ie, C00001.00 -the SubjectID assigned in the NLSY79-Children files). However for Gen1 subjects, the SubjectTag is their CaseID (ie, R00001.00), with "00" appended. This manipulation is necessary to identify subjects uniquely in inter-generational datasets. A Gen1 subject with an ID of 43 has a SubjectTag of 4300. The SubjectTags of her four children remain 4301, 4302, 4303, and 4304. Level 5 of RelationshipPath (ie, AuntNiece) is gender neutral. The relationship could be either Aunt-Niece, Aunt-Nephew, Uncle-Niece, or Uncle-Nephew. If there's a widely-accepted gender-neutral term, please tell me. MZ twins have R=1. DZ twins and full-siblings have R=.5. Half-siblings have R=.25. Typical first-cousins have R=.125 Unrelated subjects have R=0 (this occasionally happens for Gen1Housemates). Other R coefficients are possible. ??Joe, do you have an earlier paper that enumerates all the obscure combinations, like half-cousins or an ambiguous AuntNiece??

References

The NLSY79 variable HHID (ie, R00001.49) is the source for the ExtendedID variable. This is discussed at http://www.nlsinfo.org/nlsy79/docs/79html/79text/hhcomp.htm. ** We need an introduction reference/information for 'R'/Relatedness. **

See Also

The LinksPair79 dataset contains columns necessary for a basic BG analysis. The Links79PairExpanded dataset contains further information that might be useful in more complicated BG analyses. A tutorial that produces a similar dataset is http://www.nlsinfo.org/childya/nlsdocs/tutorials/linking_mothers_and_children/linking_mothers_and_children_tutorial.html. It provides examples in SAS, SPSS, and STATA. The current dataset (ie, Links79Pair) can be saved as a CSV file (comma-separated file) and imported into in other programs and languages. In the R console, type the following two lines of code: library(NlsyLinks); data(Links79Pair) write.csv(Links79Pair, "C:/BGDirectory/Links79Pair.csv") where "C:/BGDirectory/" is replaced by your preferred directory. Remember to use forward slashes instead of backslashes; for instance, the path "C:\BGDirectory\Links79Pair.csv" will be misinterpreted.

Examples

library(NlsyLinks) #Load the package into the current R session.
data(Links79Pair)  #Load the dataset from the NlsyLinks package.
summary(Links79Pair)  #Summarize the five variables.
hist(Links79Pair$R)  #Display a histogram of the Relatedness coefficients.
table(Links79Pair$R)  #Create a table of the Relatedness coefficients for the whole sample.

#Create a dataset of only Gen2 sibs, and display the distribution of R.
gen2Siblings <- subset(Links79Pair, RelationshipPath=='Gen2Siblings')
table(gen2Siblings$R)  #Create a table of the Relatedness coefficients for the Gen2 sibs.