reliability_summary: Reliability Analysis

In psycModel: Integrated Toolkit for Psychological Analysis and Modeling in R

Reliability Analysis

Description

First, it will determine whether the data is uni-dimensional or multi-dimensional using parameters::n_factors(). If the data is uni-dimensional, then it will print a summary consists of alpha, G6, single-factor CFA, and descriptive statistics result. If it is multi-dimensional, it will print a summary consist of alpha, G6, omega result. You can bypass this by specifying the dimensionality argument.

Usage

reliability_summary(
  data,
  cols,
  dimensionality = NULL,
  digits = 3,
  descriptive_table = TRUE,
  quite = FALSE,
  streamline = FALSE,
  return_result = FALSE
)

Arguments

data	data.frame
cols	items for reliability analysis. Support dplyr::select() syntax.
dimensionality	Specify the dimensionality. Either uni (uni-dimensionality) or multi (multi-dimensionality). Default is NULL that determines the dimensionality using EFA.
digits	number of digits to round to
descriptive_table	Get descriptive statistics. Default is TRUE
quite	suppress printing output
streamline	print streamlined output
return_result	If it is set to TRUE (default is FALSE), it will return psych::alpha for uni-dimensional scale, and psych::omega for multidimensional scale.

Value

a psych::alpha object for unidimensional scale, and a psych::omega object for multidimensional scale.

Examples

fit <- reliability_summary(data = lavaan::HolzingerSwineford1939, cols = x1:x3)
fit <- reliability_summary(data = lavaan::HolzingerSwineford1939, cols = x1:x9)

psycModel documentation built on Nov. 2, 2023, 6:02 p.m.