lassoSelect: Update lvnatLasso results to select a different model

In lvnet: Latent Variable Network Modeling

Description

This function can be used to select a model using any fit index

Usage

lassoSelect(object, select, minimize = TRUE, refit = TRUE, lassoTol = 1e-04)

Arguments

object	An lvnetLasso object
select	A raw R expression using names used in the object$fitMeasures part of the output of lvnet
minimize	Logical. Minimize or maximize?
refit	Logical. Should the new best model be refitted.
lassoTol	Tolerance for absolute values to be treated as zero in counting parameters.

Author(s)

Sacha Epskamp <[e-mail]>

Examples

## Not run: 
# Load dataset:
library("lavaan")
data(HolzingerSwineford1939)
Data <- HolzingerSwineford1939[,7:15]

# Measurement model:
Lambda <- matrix(0, 9, 3)
Lambda[1:3,1] <- NA
Lambda[4:6,2] <- NA
Lambda[7:9,3] <- NA

# Search best fitting omega_theta:
res <- lvnetLasso(Data, "omega_theta", lambda = Lambda)
res$best
summary(res)

# Update to use EBIC:
resEBIC <- lassoSelect(res, ebic)
summary(resEBIC)

# Update to use minimal fitting model with RMSEA < 0.05:
resMinimal <- lassoSelect(res, df * (rmsea < 0.05), minimize = FALSE)
summary(resMinimal)

## End(Not run)

lvnet documentation built on June 21, 2019, 9:06 a.m.