The example data | Working with rows and columns | Joins | Matrix operations | PCA, clustering and MDS | Statistics for every row or column | Plotting and exporting | Where next

Mutating joins on rows | Left join: add columns, keep every respondent | Inner join: keep only respondents with a match | Right and full joins: new rows get NA in the matrix | Filtering joins | Joins on columns | Joining on differently named keys | Duplicate keys | Joins and stored analyses | See also

Summary statistics into metadata | Custom transformations with transform_matrix() | Reverse-scoring items | Whole-matrix transformations | Column- and row-wise transformations | Centering and scaling | Standardising items | Removing response style | Clipping | Log transformation | Transposing | Getting the matrix out | Matrix operations and stored analyses | See also

Creating Example Data | Classical Multidimensional Scaling (MDS) | Accessing Stored MDS Object | t-SNE (t-distributed Stochastic Neighbor Embedding) | t-SNE Parameters | UMAP (Uniform Manifold Approximation and Projection) | UMAP Parameters | Comparing Methods | Gene-Level Dimensionality Reduction | Multiple Dimensions | Using with to_long() | Summary

Data | PCA | Which way? | PCA on respondents | PCA on items | Hierarchical clustering | Clustering items | Clustering respondents | k-means | Profiling clusters | Comparing clusterings | Managing stored analyses | When stored analyses are dropped | See also

Data | Plotting metadata | PCA of respondents | PCA of items | Relationships between metadata variables | Test results | Plotting individual values with to_long() | Heatmaps | Respondents × items | Aggregated heatmap | Exporting | The matrix | The metadata | Everything at once | See also

Data | Comparing two groups | t-test | Wilcoxon test | Continuous variables | Correlation | Simple regression | Multiple regression | More than two groups | Your own function: compute_across() | Row-wise statistics | Storing results in the metadata | See also

Activation | Filtering | Adding and changing metadata | Selecting, renaming and relocating metadata columns | Reordering | Slicing | Grouping and summarising | Summarising columns: one score per trait | Summarising rows: group profiles | Other aggregation functions | Counting | Putting it together | A note on stored analyses

Creating Example Data | Classical Multidimensional Scaling (MDS) | Accessing Stored MDS Object | t-SNE (t-distributed Stochastic Neighbor Embedding) | t-SNE Parameters | UMAP (Uniform Manifold Approximation and Projection) | UMAP Parameters | Comparing Methods | Gene-Level Dimensionality Reduction | Multiple Dimensions | Using with to_long() | Summary

The example data | Working with rows and columns | Joins | Matrix operations | PCA, clustering and MDS | Statistics for every row or column | Plotting and exporting | Where next

Mutating joins on rows | Left join: add columns, keep every respondent | Inner join: keep only respondents with a match | Right and full joins: new rows get NA in the matrix | Filtering joins | Joins on columns | Joining on differently named keys | Duplicate keys | Joins and stored analyses | See also

Summary statistics into metadata | Custom transformations with transform_matrix() | Reverse-scoring items | Whole-matrix transformations | Column- and row-wise transformations | Centering and scaling | Standardising items | Removing response style | Clipping | Log transformation | Transposing | Getting the matrix out | Matrix operations and stored analyses | See also

Data | PCA | Which way? | PCA on respondents | PCA on items | Hierarchical clustering | Clustering items | Clustering respondents | k-means | Profiling clusters | Comparing clusterings | Managing stored analyses | When stored analyses are dropped | See also

Data | Plotting metadata | PCA of respondents | PCA of items | Relationships between metadata variables | Test results | Plotting individual values with to_long() | Heatmaps | Respondents × items | Aggregated heatmap | Exporting | The matrix | The metadata | Everything at once | See also

Data | Comparing two groups | t-test | Wilcoxon test | Continuous variables | Correlation | Simple regression | Multiple regression | More than two groups | Your own function: compute_across() | Row-wise statistics | Storing results in the metadata | See also

Activation | Filtering | Adding and changing metadata | Selecting, renaming and relocating metadata columns | Reordering | Slicing | Grouping and summarising | Summarising columns: one score per trait | Summarising rows: group profiles | Other aggregation functions | Counting | Putting it together | A note on stored analyses