A simple multiple-group ACE model with the lavaan package.
This function uses the lavaan package to estimate a univariate ACE model, using multiple groups.
Each group has a unique value of
R (i.e., the Relatedness coefficient).
Should the A variance component be estimated? A^2 represents the proportion of variability due to a shared genetic influence.
Should the C variance component be estimated? C^2 represents the proportion of variability due to a shared environmental influence.
Indicates if the estimated parameters and fit statistics are printed to the console.
The variance component for E is always estimated, while the A and C estimates can be fixed to zero (when
estimateA and/or estimateC are set to
Currently, the variables in
dsClean must be named
R; the letter ‘O’ stands for Outcome. This may not be as restrictive as it initially seems, because
dsClean is intented to be produced by
CleanSemAceDataset. If this is too restrictive for your uses, we'd like to here about it (please email wibeasley at hotmail period com).
The lavaan package is developed by Yves Rosseel at Ghent University. Three good starting points are the package home page (http://lavaan.ugent.be/), the documentation (http://cran.r-project.org/package=lavaan) and the JSS paper.
Rosseel, Yves (2012), lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48, (2), 1-36.
CleanSemAceDataset. Further ACE model details are discussed in our package's vignettes.
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library(NlsyLinks) #Load the package into the current R session. dsLinks <- Links79PairExpanded #Start with the built-in data.frame in NlsyLinks dsLinks <- dsLinks[dsLinks$RelationshipPath=='Gen2Siblings', ] #Use only Gen2 Siblings (NLSY79-C) oName_S1 <- "MathStandardized_S1" #Stands for Outcome1 oName_S2 <- "MathStandardized_S2" #Stands for Outcome2 dsGroupSummary <- RGroupSummary(dsLinks, oName_S1, oName_S2) dsClean <- CleanSemAceDataset(dsDirty=dsLinks, dsGroupSummary, oName_S1, oName_S2) ace <- AceLavaanGroup(dsClean) ace #Should produce: #  "Results of ACE estimation: [show]" # ASquared CSquared ESquared CaseCount # 0.6681874 0.1181227 0.2136900 8390.0000000 library(lavaan) #Load the package to access methods of the lavaan class. GetDetails(ace) #Exmaine fit stats like Chi-Squared, RMSEA, CFI, etc. fitMeasures(GetDetails(ace)) #The function 'fitMeasures' is defined in the lavaan package. #Examine low-level details like each group's individual parameter estimates and standard errors. summary(GetDetails(ace)) #Extract low-level details. This may be useful when programming simulations. inspect(GetDetails(ace), what="converged") #The lavaan package defines 'inspect'. inspect(GetDetails(ace), what="coef")
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