predict_DP

Character. Name of stan variable corresponding to DP weights.

Function. The density base function used.

dens

Character vector. Names of base/kernel function parameters in Stan (e.g., mu, sigma for normal base functions).

params

Character vector. Names of corresponding parameters for the R equivalent (e.g., mean, sd in dnorm).

R_params

Prediction for DP density estimation models.

internal

Estimates random effect latent measurement models, wherein the loadings, residual variances, intercepts, latent means, and latent variances all vary across groups. The random effect variances of the measurement parameters are then modeled using a hierarchical inclusion model, wherein the inclusion of the variances (i.e., whether it is effectively zero or non-zero) is informed by similar parameters (of the same type, or of the same item). This additional hierarchical structure allows the evidence in favor of partial invariance to accumulate more quickly, and yields more certain decisions about measurement invariance. Martin, Williams, and Rast (2020) <doi:10.31234/osf.io/qbdjt>.

predict_DP: Prediction for DP density estimation models.

Description

Usage

Arguments

Value