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

print output is stable

Code
  print(efa_reliability(sl_mod, factor_map = fc))
Output

  Total variance from the correlation matrix.

  -- Reliability coefficients ----------------------------------------------------

       tot  hier   sub  alpha    H
  g <num> <num> <num> <num> <num>
  F1 <num> <num> <num> <num> <num>
  F2 <num> <num> <num> <num> <num>
  F3 <num> <num> <num> <num> <num>

  -- Common-variance indices -----------------------------------------------------

      ECV   PUC
  g <num> <num>

Code
  print(efa_reliability(sl_mod, factor_map = fc, coefficients = c("omega_total",
    "alpha")))
Output

  Total variance from the correlation matrix.

  -- Reliability coefficients ----------------------------------------------------

       tot  alpha
  g <num> <num>
  F1 <num> <num>
  F2 <num> <num>
  F3 <num> <num>

Code
  print(efa_reliability(efa_mod))
Output

  Total variance from the correlation matrix.

  Correlated-factors solution: a factor's total omega counts the true score
  variance its composite receives from every factor, through its cross-loadings
  and any factor correlations; its subscale omega counts only that factor's own
  contribution.

  -- Reliability coefficients ----------------------------------------------------

          tot   sub  alpha    H
  total <num> <num>
  F1 <num> <num> <num> <num>
  F2 <num> <num> <num> <num>
  F3 <num> <num> <num> <num>

the model error names the averaged matrix an efa_average object carries

Code
  cat(conditionMessage(e))
Output
  Invalid `model`.
  i Enter a <lavaan>, `psych::schmid()`, <SL>, or <EFA> object, a bifactor loading matrix, or specify `var_names`, `g_load`, `s_load`, and `u2`.
  i From an <efa_average> object, use the averaged loading matrix in `$loadings$average`, with `$Phi$average` as `Phi` and `$orig_R` as `cormat`.