simulate_DP

Data.frame of parameters corresponding to d and r distribution functions. (E.g., data.frame(mean = rnorm(50), sd = abs(rnorm(50, 0, .5))))

param

Numeric. The alpha parameter to the DP.

alpha

Character. Root name of base or kernel function (e.g., "norm", "exp").

Generate Truncated Dirichlet Process Mixture.

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>.

simulate_DP: Generate Truncated Dirichlet Process Mixture.

Description

Usage

Arguments

Value