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Effect sizes: maximal models, fitted pilots, and safeguard power2 days ago
Maximal models: correlated random slopes | Power from a fitted pilot model | Planning around a smallest effect size of interest | Safeguard power | Reading Type S and Type M errors
mixpower 1.1.1Alex Litovchenko mixpower-effect-sizes.Rmd
Extending mixpower with custom backends2 days ago
The three-function contract | Building a validated backend with mp_backend() | Using mp_scenario() and mp_power() | Built-in backends | Parallel grids | Further reading
mixpower 1.1.1Alex Litovchenko mixpower-extending.Rmd
mixpower intro2 days ago
Inference options: Wald vs LRT | Binary outcomes (binomial GLMM) | Sensitivity curve for binomial outcomes | Count outcomes (Poisson vs Negative Binomial) | Sensitivity curves (count outcomes)
mixpower 1.1.1Alex Litovchenko mixpower-intro.Rmd
Reproducibility workflow2 days ago
Run analysis and capture manifest | Bundle results and export | Regenerating from manifest and seed | One-row manifest for saving
mixpower 1.1.1Alex Litovchenko mixpower-reproducibility.Rmd
Validation: is your power number trustworthy?2 days ago
Calibrate: does the test hold its alpha? | Catching a misspecified model | Recommend: which inference method? | Reporting
mixpower 1.1.1Alex Litovchenko mixpower-validation.Rmd
Designing studies7 days ago
mixpower 1.1.1Alex Litovchenko mixpower-design.Rmd
Diagnostics and sensitivity7 days ago
mixpower 1.1.1Alex Litovchenko mixpower-diagnostics.Rmd
Running simulations7 days ago
mixpower 1.1.1Alex Litovchenko mixpower-simulations.Rmd
Glossary and quick-start checklist7 days ago
Glossary of main functions | Quick-start checklist | Wide input (strict and explicit) | Comparison with generic workflows
tidyILD 0.4.1tidyILD authorsild-glossary-and-quickstart.Rmd
Glossary and quick-start checklist2 months ago
Glossary of main functions | Quick-start checklist | Wide input (strict and explicit) | Comparison with generic workflows
tidyILD 0.4.1tidyILD authorsild-glossary-and-quickstart.Rmd
Bayesian dynamics recipes (ild_brms)2 months ago
Prerequisites | Recipe 1: Random slope for a lagged predictor | Recipe 2: Bivariate lag sketch (two variables) | Recipe 3: Multivariate outcomes with mvbind (sketch) | See also
tidyILD 0.4.1tidyILD authorsbrms-dynamics-recipes.Rmd
Choosing between lme/nlme, brms, KFAS, and ctsem2 months ago
Decision axes | Comparison table | Short pointers to other vignettes | See also
tidyILD 0.4.1Alex Litovchenkokfas-choosing-backend.Rmd
Continuous-Time Dynamics with ctsem in tidyILD2 months ago
When to use ild_ctsem() | Minimal workflow | Diagnostics and plots | Guardrails and reporting | Notes
tidyILD 0.4.1tidyILD authorsctsem-continuous-time-dynamics.Rmd
Developer contracts (package standards)2 months ago
See also
tidyILD 0.4.1Alex Litovchenko developer-contracts.Rmd
From raw data to model with tidyILD2 months ago
Simulate and prepare | Inspect | Within-person centering and lags | Fit a model | Diagnostics and plots | MSM-style weights (IPTW and IPCW) — optional | Reproducibility
tidyILD 0.4.1tidyILD authorstidyILD-workflow.Rmd
Heterogeneity and person-specific effects2 months ago
Estimands: population, partial pooling, and no pooling | ild_heterogeneity() | Diagnostics bundle and plots | Stratified descriptive comparison | See also
tidyILD 0.4.1Alex Litovchenko heterogeneity-interpretation.Rmd
Irregular measurement and latent state tracking2 months ago
Motivation | What ild_kfas() assumes today | irregular_time and guardrails | Workflow sketch | Where to go next
tidyILD 0.4.1Alex Litovchenkokfas-irregular-timing-spacing.Rmd
Missingness in ILD: diagnostics and sensitivity routes2 months ago
Why missingness matters in intensive longitudinal data | Types of missingness (useful labels) | Descriptive profiling: ild_missing_pattern() and heatmaps | Person-level compliance: ild_missing_compliance() | When to use ild_missing_model() and ild_missing_bias() | Complete-case vs mixed models (careful wording) | Cohort-level and hazard summaries | One entry point: ild_missingness_report() | MNAR as sensitivity (no single fix) | IPW and causal tools as one sensitivity route | Other templates (not evaluated here) | What tidyILD does not do (and where to look) | See also
tidyILD 0.4.1Alex Litovchenko ild-missingness-workflow.Rmd
MSM Identification and Recovery in tidyILD2 months ago
Why this vignette exists | Identification assumptions | Estimand-first + history-builder workflow (v1) | Recovery harness | Inference caveats and strict mode | Notes on v1 scope
tidyILD 0.4.1Alex Litovchenko msm-identification-and-recovery.Rmd
Short analysis report2 months ago
1. Fit model(s) | 2. Tidy fixed-effects table | 3. Fitted vs observed | 4. Residual diagnostics: ACF and Q-Q | With AR1 (nlme) | Time-varying effects (TVEM)
tidyILD 0.4.1Alex Litovchenkoild-analysis-report.Rmd
Simulation benchmarks: recovery and power2 months ago
Simulation size and precision | What ild_simulate() encodes | Fixed-effect recovery with ild_power(..., return_sims = TRUE) | From recovery to power | Variance components (illustrative snapshot) | AR(1) in the DGP vs residual correlation in the fit | Bayesian and state-space extensions | Cross-backend validation harness (optional) | Limitations and scope | See also
tidyILD 0.4.1tidyILD authorsbenchmark-simulation-recovery.Rmd
Specialist backends: when to move beyond the default stack2 months ago
Contract: what tidyILD owns vs what it does not | Decision table | Handoff pattern: export after prepare, center, and lag | Code stubs (not evaluated) | dynamite (multivariate dynamic models) | PGEE (penalized GEE / high-dimensional longitudinal) | lavaan / blavaan (DSEM) | See also
tidyILD 0.4.1tidyILD authorsild-specialist-backends.Rmd
State-space modeling in tidyILD with KFAS2 months ago
What is a state-space model? | When use this instead of mixed-model residual correlation? | Filtered vs smoothed states | Minimal example | What the backend does not yet do | See also
tidyILD 0.4.1Alex Litovchenkokfas-state-space-modeling.Rmd
Temporal dynamics: choosing a model for ILD2 months ago
Three axes before you fit anything | Decision flow (conceptual) | Feature map | Minimal examples | Further reading
tidyILD 0.4.1tidyILD authorstemporal-dynamics-model-choice.Rmd
Tsibble interoperability2 months ago
Ingesting a tsibble with ild_prepare() | What provenance is kept | How to inspect | Round-trip with ild_as_tsibble() | Limitations and policy
tidyILD 0.4.1tidyILD authorstsibble-interoperability.Rmd
Visualization in tidyILD2 months ago
Role of visual inspection | Map: question → function → bundle section (if any) | Example: spaghetti, predicted trajectories, facet by cluster | Recipe: facet panels without a dedicated helper | Partial effects for _wp and _bp (external packages) | See also
tidyILD 0.4.1Alex Litovchenko visualization-in-tidyILD.Rmd
Within-between decomposition and handling irregular spacing2 months ago
Within-between decomposition | Irregular spacing and lags | Spacing classification
tidyILD 0.4.1tidyILD authorsild-decomposition-and-spacing.Rmd
Bayesian dynamics recipes (ild_brms)2 months ago
Prerequisites | Recipe 1: Random slope for a lagged predictor | Recipe 2: Bivariate lag sketch (two variables) | Recipe 3: Multivariate outcomes with mvbind (sketch) | See also
tidyILD 0.4.1tidyILD authorsbrms-dynamics-recipes.Rmd
Specialist backends: when to move beyond the default stack2 months ago
Contract: what tidyILD owns vs what it does not | Decision table | Handoff pattern: export after prepare, center, and lag | Code stubs (not evaluated) | dynamite (multivariate dynamic models) | PGEE (penalized GEE / high-dimensional longitudinal) | lavaan / blavaan (DSEM) | See also
tidyILD 0.4.1tidyILD authorsild-specialist-backends.Rmd
Temporal dynamics: choosing a model for ILD2 months ago
Three axes before you fit anything | Decision flow (conceptual) | Feature map | Minimal examples | Further reading
tidyILD 0.4.1tidyILD authorstemporal-dynamics-model-choice.Rmd
Visualization in tidyILD2 months ago
Role of visual inspection | Map: question → function → bundle section (if any) | Example: spaghetti, predicted trajectories, facet by cluster | Recipe: facet panels without a dedicated helper | Partial effects for _wp and _bp (external packages) | See also
tidyILD 0.4.1Alex Litovchenko visualization-in-tidyILD.Rmd
Heterogeneity and person-specific effects3 months ago
Estimands: population, partial pooling, and no pooling | ild_heterogeneity() | Diagnostics bundle and plots | Stratified descriptive comparison | See also
tidyILD 0.4.1Alex Litovchenko heterogeneity-interpretation.Rmd
Missingness in ILD: diagnostics and sensitivity routes3 months ago
Why missingness matters in intensive longitudinal data | Types of missingness (useful labels) | Descriptive profiling: ild_missing_pattern() and heatmaps | Person-level compliance: ild_missing_compliance() | When to use ild_missing_model() and ild_missing_bias() | Complete-case vs mixed models (careful wording) | Cohort-level and hazard summaries | One entry point: ild_missingness_report() | MNAR as sensitivity (no single fix) | IPW and causal tools as one sensitivity route | Other templates (not evaluated here) | What tidyILD does not do (and where to look) | See also
tidyILD 0.4.1Alex Litovchenko ild-missingness-workflow.Rmd
Within-between decomposition and handling irregular spacing3 months ago
Within-between decomposition | Irregular spacing and lags | Spacing classification
tidyILD 0.4.1tidyILD authorsild-decomposition-and-spacing.Rmd
Choosing between lme/nlme, brms, KFAS, and ctsem3 months ago
Decision axes | Comparison table | Short pointers to other vignettes | See also
tidyILD 0.4.1Alex Litovchenkokfas-choosing-backend.Rmd
From raw data to model with tidyILD3 months ago
Simulate and prepare | Inspect | Within-person centering and lags | Fit a model | Diagnostics and plots | MSM-style weights (IPTW and IPCW) — optional | Reproducibility
tidyILD 0.4.1tidyILD authorstidyILD-workflow.Rmd
Simulation benchmarks: recovery and power3 months ago
Simulation size and precision | What ild_simulate() encodes | Fixed-effect recovery with ild_power(..., return_sims = TRUE) | From recovery to power | Variance components (illustrative snapshot) | AR(1) in the DGP vs residual correlation in the fit | Bayesian and state-space extensions | Cross-backend validation harness (optional) | Limitations and scope | See also
tidyILD 0.4.1tidyILD authorsbenchmark-simulation-recovery.Rmd
Continuous-Time Dynamics with ctsem in tidyILD3 months ago
When to use ild_ctsem() | Minimal workflow | Diagnostics and plots | Guardrails and reporting | Notes
tidyILD 0.4.1tidyILD authorsctsem-continuous-time-dynamics.Rmd
MSM Identification and Recovery in tidyILD3 months ago
Why this vignette exists | Identification assumptions | Estimand-first + history-builder workflow (v1) | Recovery harness | Inference caveats and strict mode | Notes on v1 scope
tidyILD 0.4.1Alex Litovchenko msm-identification-and-recovery.Rmd
Short analysis report3 months ago
1. Fit model(s) | 2. Tidy fixed-effects table | 3. Fitted vs observed | 4. Residual diagnostics: ACF and Q-Q | With AR1 (nlme) | Time-varying effects (TVEM)
tidyILD 0.4.1Alex Litovchenkoild-analysis-report.Rmd
Tsibble interoperability3 months ago
Ingesting a tsibble with ild_prepare() | What provenance is kept | How to inspect | Round-trip with ild_as_tsibble() | Limitations and policy
tidyILD 0.4.1tidyILD authorstsibble-interoperability.Rmd
Irregular measurement and latent state tracking3 months ago
Motivation | What ild_kfas() assumes today | irregular_time and guardrails | Workflow sketch | Where to go next
tidyILD 0.4.1Alex Litovchenkokfas-irregular-timing-spacing.Rmd
State-space modeling in tidyILD with KFAS3 months ago
What is a state-space model? | When use this instead of mixed-model residual correlation? | Filtered vs smoothed states | Minimal example | What the backend does not yet do | See also
tidyILD 0.4.1Alex Litovchenkokfas-state-space-modeling.Rmd
Developer contracts (package standards)3 months ago
See also
tidyILD 0.4.1Alex Litovchenko developer-contracts.Rmd
Reproducible ILD workflows with tidyILD provenance3 months ago
1. Prepare data | 2. Center and lag | 3. Fit model | 4. Run diagnostics | 5. Inspect ild_history() | 6. Generate ild_methods() | 7. Run ild_report() | 8. Export provenance | 9. Compare two pipelines
tidyILD 0.4.1Alex Litovchenkoild-provenance.Rmd
Reproducible ILD workflows with tidyILD provenance4 months ago
1. Prepare data | 2. Center and lag | 3. Fit model | 4. Run diagnostics | 5. Inspect ild_history() | 6. Generate ild_methods() | 7. Run ild_report() | 8. Export provenance | 9. Compare two pipelines
tidyILD 0.4.1Alex Litovchenkoild-provenance.Rmd
Designing studies4 months ago
mixpower 0.1.0Mixpower Alex Litovchenko mixpower-design.Rmd
Diagnostics and sensitivity4 months ago
mixpower 0.1.0Mixpower Alex Litovchenko mixpower-diagnostics.Rmd
mixpower intro4 months ago
Inference options: Wald vs LRT | Binary outcomes (binomial GLMM) | Sensitivity curve for binomial outcomes | Count outcomes (Poisson vs Negative Binomial) | Sensitivity curves (count outcomes)
mixpower 0.1.0Mixpower Alex Litovchenko mixpower-intro.Rmd
Reproducibility workflow4 months ago
Run analysis and capture manifest | Bundle results and export | Regenerating from manifest and seed | One-row manifest for saving
mixpower 0.1.0Mixpower Alex Litovchenko mixpower-reproducibility.Rmd
Running simulations4 months ago
mixpower 0.1.0Mixpower Alex Litovchenko mixpower-simulations.Rmd