Computes variable-level diagnostics used to distinguish indicators that participate in a shared multivariate structure from redundant, standalone, or noisy indicators. Correlation summaries exclude each variable's correlation with itself.
Usage
fiscal_diagnostics(
data,
variables = NULL,
corr_cutoff = 0.9,
kmo_low = 0.5,
communality_low = 0.2,
mean_abs_cor_low = 0.1,
smc_high = 0.9,
vif_high = 10,
near_zero_sd = 1e-06,
nfactors_comm = NULL,
rotate = "oblimin",
fm = "minres",
use = "pairwise.complete.obs"
)Arguments
- data
A data frame containing candidate indicators.
- variables
Character vector of columns to diagnose. By default, all numeric columns are used.
- corr_cutoff
Absolute correlation used to flag redundancy.
- kmo_low
KMO/MSA threshold used to flag weak shared variance.
- communality_low
Threshold used to flag low communality.
- mean_abs_cor_low
Threshold used to flag weak connectedness.
- smc_high
Squared multiple correlation threshold.
- vif_high
Variance inflation factor threshold.
- near_zero_sd
Standard-deviation threshold for near-zero variance.
- nfactors_comm
Number of factors in the preliminary communality screen. The default is between one and three, based on the number of usable indicators.
- rotate
Rotation passed to
psych::fa().- fm
Factoring method passed to
psych::fa().- use
Missing-value rule passed to
stats::cor().