First steps | Simple Plots | Styling an object | Making Styles Stick with redefault | Apply Styles Across Shapes with ob_style | Placing Objects in Relation to Other Objects | Object Arrays with ob_array | Building Plots Sequentially in a ggplot2 Pipeline | Changing the default arrowhead

Tail Highlighting | Direction of Violin | Violin Width | Setting Limits

Calculate composite scores | Estimate expected test scores conditioned on a composite score | Calculating the Conditional Mahalanobis Distance

Univariate Outliers | Multivariate Outliers | Quantifying Multivariate Extremity | The Euclidean Distance | The Mahalanobis Distance | Conditional Mahalanobis Distances | Distinguishing Profile Shape from Profile Elevation | A Worked Example with a Simple Model | Calculations Using the simstandard and unusualprofile Packages | View Complete Output of cond_maha Function | A Worked Example with a More Complex Model | Conditional Mahalanobis Distances with Indicator Scores Only | Composite Score Model | Observed Scores, Given Composite Scores | Factor-score model | References

Tables | Load Packages and Set Defaults | Make Data | Initial Results with flextable | Polished table with apa_flextable | Conditional Formatting | Automatic formatting | Helper functions | Break columns | Column Spanners and Deckered Heads | Decimal/Character alignment | Hanging indent | Creating a numbered list | Stars | APA format with full control | Specialized tables | Regression | Correlation | Cross-tabulation with Chi-square Test of Independence | Factor Analysis | Limitations

Purpose of simstandard | Generate Model-Based Multivariate Data | Comparison with lavaan::simulateData | Inspecting model matrices | Estimated Factor Scores | Adding factor scores to new data | Composite Scores | Return lavaan syntax with all parameters set free | Return lavaan syntax for a model with standardized variances specified | Return lavaan syntax from matrices | The measurement model | The structural model | Covariances | Using the matrix2lavaan function | Specifying models with data.frames instead of matrices | Return model-implied correlation matrices