Description Usage Arguments Details Value Author(s) References Examples
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).
1 2 3 4 5 6 | 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")
|
method |
The specific estimation technique. |
dataSet |
The |
oName_S1 |
The name of the outcome variable corresponding to the first
subject in the pair. This should be a |
oName_S2 |
The name of theoutcome variable corresponding to the second
subject in the pair. This should be a |
rName |
The name of the relatedness coefficient for the pair (this is
typically abbreviated as |
manifestScale |
Currently, only continuous manifest/outcome variables are supported. |
The AceUnivariate
function is a wrapper that calls
DeFriesFulkerMethod1
or DeFriesFulkerMethod3
. Future
versions will incorporate methods that use latent variable models.
Currently, a list is returned with the arguments ASquared
,
CSquared
, ESquared
, and RowCount
. In the future, this
may be changed to an S4
class.
Will Beasley
Rodgers, Joseph Lee, & Kohler, Hans-Peter (2005). Reformulating and simplifying the DF analysis model. Behavior Genetics, 35 (2), 211-217.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | 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))
|
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