psychmeta (version 2.3.4)

var_error_alpha: Analytic estimate of the sampling variance of alpha

Description

Analytic estimate of the sampling variance of alpha

Usage

var_error_alpha(item_mat = NULL, alpha = NULL, k_items = NULL,
  n_cases)

Arguments

item_mat

Item correlation/covariance matrix. If item_mat is not supplied, the user must supply both alpha and k_items. If item_mat is NULL, the program will assume that all item intercorrelations are equal.

alpha

Vector of population alpha values. Must be supplied if item_mat is NULL.

k_items

Vector of numbers of items to be simulated. Must be supplied if item_mat is NULL.

n_cases

Vector of sample sizes to simulate in sampling distribution of alpha.

Value

Vector of sampling variances of the supplied alpha(s).

References

Duhachek, A., & Iacobucci, D. (2004). Alpha<U+2019>s standard error (ASE): An accurate and precise confidence interval estimate. Journal of Applied Psychology, 89(5), 792<U+2013>808. https://doi.org/10.1037/0021-9010.89.5.792

Examples

# NOT RUN {
item_mat <- matrix(.3, 5, 5)
diag(item_mat) <- 1
alpha <- mean(item_mat[lower.tri(item_mat)]) / mean(item_mat)
k_items <- nrow(item_mat)

var_error_alpha(item_mat = item_mat, n_cases = 50)
var_error_alpha(alpha = alpha, k_items = k_items, n_cases = 50)
var_error_alpha(alpha = c(alpha, alpha), k_items = c(k_items, k_items), n_cases = 50)
# }