NlsyLinks (version 2.2.2)

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

Description

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.

Usage

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

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.

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.

Author

Will Beasley

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.

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)

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