mtscr_model_summary: Summarise a model

In mtscr: Multidimensional Top Scoring for Creativity Research

Summarise a model

Description

Summarise a model generated with mtscr_model with some basic statistics; calculate the empirical reliability and the first difference of the empirical reliability.

Usage

mtscr_model_summary(model)

Arguments

model

A model generated with mtscr_model. Can be a list of models.

Value

A data frame with the following columns:

model

The model number

nobs

Number of observations

sigma

The square root of the estimated residual variance

logLik

The log-likelihood of the model

AIC

The Akaike information criterion

BIC

The Bayesian information criterion

df.residual

The residual degrees of freedom

emp_rel

The empirical reliability

FDI

The first difference of the empirical reliability

Examples

data("mtscr_creativity", package = "mtscr")
mtscr_model(mtscr_creativity, id, item, SemDis_MEAN, top = 1:3) |>
  mtscr_model_summary()

mtscr documentation built on Nov. 2, 2023, 5:13 p.m.