NlsyLinks (version 2.0.6)

Ace: Estimates the heritability of additive traits using a single variable.

Description

An ACE model is the foundation of most behavior genetic research. It estimates the additive heritability (with a), common environment (with c) and unshared heritability/environment (with e).

Usage

AceUnivariate(method=c("DeFriesFulkerMethod1","DeFriesFulkerMethod3"),  dataSet, oName_S1, oName_S2, rName="R", manifestScale="Continuous")
DeFriesFulkerMethod1(dataSet, oName_S1, oName_S2, rName="R")
DeFriesFulkerMethod3(dataSet, oName_S1, oName_S2, rName="R")

Arguments

method

The specific estimation technique.

dataSet

The data.frame that contains the two outcome variables and the relatedness coefficient (corresponding to oName_S1, oName_S2, and rName)

oName_S1

The name of the outcome variable corresponding to the first subject in the pair. This should be a character value.

oName_S2

The name of theoutcome variable corresponding to the second subject in the pair. This should be a character value.

rName

The name of the relatedness coefficient for the pair (this is typically abbreviated as R). This should be a character value.

manifestScale

Currently, only continuous manifest/outcome variables are supported.

Value

Currently, a list is returned with the arguments ASquared, CSquared, ESquared, and RowCount. In the future, this may be changed to an S4 class.

Details

The AceUnivariate function is a wrapper that calls DeFriesFulkerMethod1 or DeFriesFulkerMethod3. Future versions will incorporate methods that use latent variable models.

References

Rodgers, Joseph Lee, & Kohler, Hans-Peter (2005). Reformulating and simplifying the DF analysis model. Behavior Genetics, 35 (2), 211-217.

Examples

library(NlsyLinks) #Load the package into the current R session.
dsOutcomes <- ExtraOutcomes79
dsOutcomes$SubjectTag <- CreateSubjectTag(subjectID=dsOutcomes$SubjectID,
  generation=dsOutcomes$Generation)
dsLinks <- Links79Pair
dsLinks <- dsLinks[dsLinks$RelationshipPath=='Gen2Siblings', ] #Only Gen2 Sibs (ie, NLSY79C)
dsDF <- CreatePairLinksDoubleEntered(outcomeDataset=dsOutcomes, linksPairDataset=dsLinks, 
  outcomeNames=c("MathStandardized", "HeightZGenderAge", "WeightZGenderAge"))

estimatedAdultHeight <- DeFriesFulkerMethod3(
  dataSet=dsDF,    
  oName_S1="HeightZGenderAge_S1", 
  oName_S2="HeightZGenderAge_S2")  
estimatedAdultHeight #ASquared and CSquared should be 0.60 and 0.10 for this rough analysis.

estimatedMath <- DeFriesFulkerMethod3(
  dataSet=dsDF,    
  oName_S1="MathStandardized_S1", 
  oName_S2="MathStandardized_S2")
estimatedMath #ASquared and CSquared should be 0.85 and 0.045.

class(GetDetails(estimatedMath))
summary(GetDetails(estimatedMath))