rties (version 5.0.0)

sysVarIn: Provides results for predicting couples' latent profile membership from the system variable.

Description

If there are 2 profiles, then glm binomial regression models are used. If there are more than 2 profiles then multinomial regression is used (from the nnet package). The system variable can be either dyadic (sysVarType = "dyadic"), where both partners have the same score (e.g., relationship length) or individual (sysVarType = "indiv"), where the partners can have different scores (e.g., age). For dyadic system variables, a couple's shared score is the only predictor of their profile membership (called "sysVar"). For individual system variables, two models are tested, one with the main effects of both partner's system variable ("sysVarMain") and one with the main effects and their interaction ("sysVarInteract"). In both cases an intercept-only model is included as a comparison point (called "base"). The function returns a list of the full model results.

Usage

sysVarIn(fullData, sysVar_name, sysVarType, n_profiles)

Arguments

fullData

A dataframe created by the makeFullData function.

sysVar_name

The name of the variable in the dataframe that contains the system variable to be predicted by profile membership.

sysVarType

Whether the system variable is "dyadic", which means both partners have the same score, or "indiv" which means the partners can have different scores

n_profiles

The number of latent profiles.

Value

A list including the glm or multinom objects containing the full results for each model (called "models").

Examples

# NOT RUN {
data <- rties_ExampleDataShort
newData <- dataPrep(basedata=data, dyadId="couple", personId="person", 
obs_name="dial", dist_name="female", time_name="time", time_lag=2)
ic <- indivInertCoord(prepData=newData, whichModel="inertCoord")
profiles <- inspectProfiles(whichModel="inertCoord", prepData=newData, 
paramEst=ic$params, n_profiles=2)
fullData <- makeFullData(basedata=data, dyadId="couple", personId="person", 
dist_name="female", lpaData=profiles, params=ic$params)
sysIn <- sysVarIn(fullData=fullData, sysVar_name="conflict", sysVarType="indiv", n_profiles=2)
summary(sysIn$models$sysVarMain)

# }