NEST: Next eigenvalue sufficiency test

In EFAtools: Fast and Flexible Implementations of Exploratory Factor Analysis Tools

Next eigenvalue sufficiency test

Description

NEST() has been superseded by efa_nest(), which is the recommended interface going forward. It remains available and unchanged so existing code keeps working.

Usage

NEST(
  x,
  N = NA,
  alpha = 0.05,
  use = c("pairwise.complete.obs", "all.obs", "complete.obs", "everything",
    "na.or.complete"),
  cor_method = c("pearson", "spearman", "kendall", "poly", "tetra"),
  n_datasets = 1000,
  ...
)

Arguments

x	data.frame or matrix. Dataframe or matrix of raw data or matrix with correlations.
N	numeric. The number of observations. Only needed if x is a correlation matrix. Must be larger than the number of variables.
alpha	numeric. The alpha level to use (i.e., 1-alpha percentile of eigenvalues is used for reference values).
use	character. Passed to stats::cor() if raw data is given as input. Default is "pairwise.complete.obs".
cor_method	character. One of "pearson", "spearman", or "kendall", passed to stats::cor(). "poly" and "tetra" are not supported because NEST compares the data against simulated continuous reference data. Default is "pearson".
n_datasets	numeric. The number of datasets to simulate. Default is 1000.
...	Further arguments passed on to the efa_fit() fits. For example, estimator, to change the estimator (PAF is default), or one of the estimation tuning knobs (type, init_comm, criterion, criterion_type, max_iter, abs_eigen, start_method), which are repacked into an estimate_control() object so that they tune the fits exactly as they always did.

Value

An object of class efa_retention, identical to the value of efa_nest(); see there for the components.

See Also

efa_nest()

EFAtools documentation built on Aug. 21, 2026, 5:16 p.m.