Next eigenvalue sufficiency test

NEST() has been superseded by efa_nest(), which is the recommended interface going forward.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.

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()