Produces a cleaned dataset that works well with when using SEM to estimate a univariate ACE model.

Source: R/clean-sem-ace-dataset.R

This function takes a 'GroupSummary' base::data.frame (which is created by the RGroupSummary() function) and returns a base::data.frame that is used by the Ace() function.

CleanSemAceDataset(dsDirty, dsGroupSummary, oName_S1, oName_S2, rName = "R")

Arguments

dsDirty

This is the base::data.frame to be cleaned.
dsGroupSummary

The base::data.frame containing information about which groups should be included in the analyses. It should be created by the RGroupSummary() function.
oName_S1

The name of the manifest variable (in dsDirty) for the first subject in each pair.
oName_S2

The name of the manifest variable (in dsDirty) for the second subject in each pair.
rName

The name of the variable (in dsDirty) indicating the pair's relatedness coefficient.

Value

A base::data.frame with one row per subject pair. The base::data.frame contains the following variables (which can NOT be changed by the user through optional parameters):

  • R The pair's R value.

  • O1 The outcome variable for the first subject in each pair.

  • O2 The outcome variable for the second subject in each pair.

  • GroupID Indicates the pair's group membership.

Details

The function takes dsDirty and produces a new base::data.frame with the following features:

  1. Only three existing columns are retained: O1, O2, and R. They are assigned these names.

  2. A new column called GroupID is created to reflect their group membership (which is based on the R value). These values are sequential integers, starting at 1. The group with the weakest R is 1. The group with the strongest R has the largest GroupID (this is typically the MZ twins).

  3. Any row is excluded if it has a missing data point for O1, O2, or R.

  4. The base::data.frame is sorted by the R value. This helps program against the multiple-group SEM API sometimes.

Author

Will Beasley

Examples

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 NLSY79-C siblings

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, rName="R" )
summary(dsClean)

#>        R                O1               O2           GroupID     
#>  Min.   :0.2500   Min.   : 65.00   Min.   : 65.0   Min.   :1.000  
#>  1st Qu.:0.2500   1st Qu.: 90.00   1st Qu.: 90.0   1st Qu.:1.000  
#>  Median :0.5000   Median : 98.00   Median : 99.0   Median :3.000  
#>  Mean   :0.4186   Mean   : 98.24   Mean   : 98.6   Mean   :2.341  
#>  3rd Qu.:0.5000   3rd Qu.:107.00   3rd Qu.:107.0   3rd Qu.:3.000  
#>  Max.   :1.0000   Max.   :135.00   Max.   :135.0   Max.   :4.000  

dsClean$AbsDifference <- abs(dsClean$O1 - dsClean$O2)
plot(jitter(dsClean$R), dsClean$AbsDifference, col="gray70")