summary.mires: Summary method for mires object.

In MIRES: Measurement Invariance Assessment Using Random Effects Models and Shrinkage

Description

Computes summaries for MIRES objects.

Usage

## S3 method for class 'mires'
summary(object, prob = 0.95, less_than = 0.1, ...)

Arguments

object	mires object.
prob	Numeric (Default = .95). Probability mass to be contained in the highest posterior density interval.
less_than	Numeric (Default: .1; positive). Value at which to assess Pr(SD < less_than|D).
...	Not used.

Details

Computes summary tables for fixed measurement parameters (loadings, residual SDs, and intercepts) and random effect standard deviations (resd). The printed output includes the posterior mean, median, SD, and .95 (Default) highest density intervals. HDIs were chosen instead of quantile intervals because the random effect SDs can be on the boundary of zero if invariance is plausible. Additionally, other columns exist to help aid decisions about invariance:

BF01

Bayes factor of invariance (Variance = 0) to non-invariance (Variance > 0)

BF10

Bayes factor of non-invariance (Variance > 0) to invariance (Variance = 0). The inverse of BF01 for convenience

Pr(SD <= less_than)

The posterior probability that the random effect SD is less than less_than (Default: .1). Set less_than to a value below which you would consider the variance to be effectively ignorable.

BF(SD <= less_than)

The Bayes Factor comparing effectively-invariant (SD < less_than) to non-invariant (SD > less_than). Set less_than to a value below which you would consider variance to be effectively ignorable. This uses the encompassing prior approach.

Value

summary.mires object. List of meta data and summary. Summary is list of summary tables for all fixed effects parameters.

Author(s)

Stephen R. Martin

MIRES documentation built on Feb. 22, 2021, 5:10 p.m.