Ordinal Data | Screening Ordinal Data | Polychoric Correlations, DWLS, and Robust Standard Errors | Why Not Just Treat the Items as Continuous? | Missing Data | Two-Stage Full-Information Maximum Likelihood | Multiple Imputation with efa_mi() | Ordinal and Missing Data | The Effective Sample of a Polychoric DWLS Fit | Keeping Both the Ordinal Treatment and the Cases | Where to Next

Screening the Data | Deciding How Many Factors to Retain | Calling Individual Criteria | Running Several Criteria at Once with efa_retain() | Extracting Factors with efa_fit() | Comparing Solutions with efa_compare() | Averaging Across Analytic Choices with efa_average() | Factor Scores with efa_scores() | Schmid-Leiman Transformation and McDonald's Omegas | Schmid-Leiman Transformation | McDonald's Omegas | Where to Next

Why the efa_* Interface | The Old-to-New Mapping | Migrating from EFA() to efa_fit() | What the type Presets Replicate | Returned Objects Keep Their Legacy Classes | Where to Next