lassoSelect function

Update lvnatLasso results to select a different model

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

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 mail@sachaepskamp.com

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)