Package: circumplex 2.0.1.9000

1. Overview | 2. Why a Bayesian SSM? | 3. The cosine model as a linear regression | 4. Fitting the model with brms | 5. From posterior draws to SSM summaries | 6. The induced prior on amplitude | Wrap-up

1. Overview | 2. The question growth modeling answers | 3. From repeated measures to a long table | 4. One joint model, not three separate ones | 5. From fixed effects to $(a(t), d(t))$ with intervals | 6. Certification: when $d(t)$ intervals are not interpretable | 7. A caution about REML intervals at small samples | 8. The unwrap alternative: angle_unwrap() | 9. Caveats and upgrades | 10. The same model in nlme and brms | Wrap-up | References

1. Overview | 2. Two questions about group differences | 3. Invariance-gated latent contrasts | 4. When to trust it: limitations | 5. Relation to the literature | Wrap-up | References

1. Overview | 2. Why a latent SSM? | 3. The measurement model | 4. Estimating a latent profile | 5. Where the confidence intervals come from | 6. What the parameters mean now | Wrap-up | References

1. Overview | 2. The circular canvas | 3. The coordinate system | Moving the center | Moving the amplitude axis | 4. Placing SSM results in the circle | 5. Restyling the canvas | 6. Composing custom layers | 7. The latent circumplex from a CPM fit | Estimated angles as ticks on the rim | Measure points on the same rim | One measure with its amplitude and displacement | The fitted correlation function | A joint confidence ellipse from posterior draws | 8. Trajectories across occasions | The same change as movement on the circle | 9. The angle axis for linear plots | 10. Relationship to the built-in plots | Wrap-up | References

1. Overview | 2. What is axis reliability? | 3. A worked example | 4. Reading the components | 5. Starting from a published correlation matrix | Wrap-up | References

1. Overview | 2. When a fit sits at a boundary | Wrap-up

1. Overview | 2. Two questions to ask before interpreting an SSM analysis | 3. Does the instrument fit a circumplex? | Fitting the circular process model | Reading the fit indices | Comparing model variants | Wrap-up | References

1. Overview | 2. The correction for the correlation metric | 3. Missing data | 4. Boundary fits | 5. Blockwise instruments | 6. The standard error of measurement | Wrap-up | References

1. Overview | 2. What Zimmermann & Wright (2017) found | 3. Simulating coverage for your own analysis | The full report | 4. When to trust SSM parameters | Wrap-up | References

1. Overview | 2. Generalizing the basic analyses | Generalizing to multiple means | Generalizing to multiple measures | Generalizing to multiple groups and multiple measures | 3. Contrast analyses | Contrasts between groups' means | Contrasts between measures in a group | Contrasts between groups' correlations | 4. Taxonomy of analysis types | 5. Working with SSM tables | Basic customizations of tables | 6. Working with SSM figures | Exporting figures as files | Wrap-up | References

1. Overview | 2. Does the instrument have circumplex structure at all? | The five tests | Where the cutoffs come from | Reading the classifications | How this complements the CPM fit | 3. Ipsatization and what it costs | Wrap-up | References

1. Overview | 2. Background and Motivation | Circumplex models, scales, and data | The Structural Summary Method | Understanding the SSM parameters | 3. Example data: jz2017 | 4. Mean-based SSM Analysis | Conducting SSM for a group's mean scores | Visualizing the results with a table and figure | 5. Correlation-based SSM Analysis | Conducting SSM for a group's correlations with an external measure | Wrap-up | References

1. Overview | 2. Loading and Examining Instrument Objects | Previewing the available instruments | Loading a specific instrument | Examining an instrument in-depth | 3. Instrument-related Tidying Functions | Ipsatizing item-level data | Scoring item-level data | Standardizing scale-level data | Wrap-up