Tidy Intensive Longitudinal Data Analysis
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Documentation for package ‘tidyILD’ version 0.4.0
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| tidyILD-package | tidyILD: Tidy Intensive Longitudinal Data Analysis |
-- A --
| as_ild | Coerce to ILD object |
| augment.ild_lme | Tidy and augment ild_lme fits with broom.mixed |
| augment_ild_model | Augment an ILD model fit with fitted values and residuals |
-- B --
| broom_ild_lme | Tidy and augment ild_lme fits with broom.mixed |
-- E --
| ema_example | Example EMA-style intensive longitudinal dataset |
-- G --
| guardrail_registry | Guardrail rule registry (analysis safety layer) |
-- I --
| ild_acf | Autocorrelation function for ILD variables or model residuals |
| ild_align | Align a secondary stream to primary ILD within a time window |
| ild_as_tsibble | Convert an ILD object to a tsibble |
| ild_augment | Augment observations with fitted values and residuals (S3 generic) |
| ild_augment.brmsfit | Augment observations with fitted values and residuals (S3 generic) |
| ild_augment.default | Augment observations with fitted values and residuals (S3 generic) |
| ild_augment.ild_fit_ctsem | Augment observations with fitted values and residuals (S3 generic) |
| ild_augment.ild_fit_kfas | Augment observations with fitted values and residuals (S3 generic) |
| ild_augment.lme | Augment observations with fitted values and residuals (S3 generic) |
| ild_augment.lmerMod | Augment observations with fitted values and residuals (S3 generic) |
| ild_augment_schema | Column dictionary for 'ild_augment()' outputs |
| ild_augment_states | Per-row latent states (long format) for complex multi-state models |
| ild_autoplot | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.brmsfit | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.default | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.ild_diagnostics | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.ild_diagnostics_bundle | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.ild_fit_ctsem | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.ild_fit_kfas | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.ild_heterogeneity | Heterogeneity and person-specific effects from mixed models |
| ild_autoplot.lme | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_autoplot.lmerMod | Autoplot for ILD model fits or diagnostics (S3 generic) |
| ild_brms | Fit a Bayesian mixed model to ILD data with 'brms' |
| ild_brms_dynamics_formula | Template brms formula for person-varying lag slope |
| ild_build_msm_history | Build MSM lagged history columns from a spec |
| ild_bundle | Bundle a result with a reproducibility manifest |
| ild_center | Within-person and between-person decomposition (centering) |
| ild_center_plot | Standalone WP/BP centering plot |
| ild_check_lags | Check lag variable validity (gap-aware) |
| ild_circadian | Time-of-day pattern plot for ILD (circadian-style) |
| ild_compare_fits | Compare fitted models (AIC, BIC, nobs) |
| ild_compare_pipelines | Compare provenance of two objects and report differences |
| ild_crosslag | Cross-lag model: lag predictor then fit outcome ~ lag |
| ild_ctsem | Fit a continuous-time state-space model via ctsem |
| ild_decomposition | Within-person and between-person variance decomposition |
| ild_design_check | ILD design diagnostics: spacing, WP/BP, missingness, and recommendations |
| ild_diagnose | Engine-agnostic diagnostics façade |
| ild_diagnose.brmsfit | Engine-agnostic diagnostics façade |
| ild_diagnose.default | Engine-agnostic diagnostics façade |
| ild_diagnose.ild_fit_ctsem | Engine-agnostic diagnostics façade |
| ild_diagnose.ild_fit_kfas | Engine-agnostic diagnostics façade |
| ild_diagnose.lme | Engine-agnostic diagnostics façade |
| ild_diagnose.lmerMod | Engine-agnostic diagnostics façade |
| ild_diagnostics | Residual diagnostics for an ILD model |
| ild_diagnostics_bundle | Canonical ILD diagnostics bundle |
| ild_diagnostics_utilities | Standalone diagnostics utilities and bundle section providers |
| ild_export_provenance | Export provenance to a JSON or YAML file |
| ild_fit | Fit a mixed model to ILD data (unified entry point) |
| ild_heatmap | ILD heatmap (alias for ild_plot with type = "heatmap") |
| ild_heterogeneity | Heterogeneity and person-specific effects from mixed models |
| ild_heterogeneity.brmsfit | Heterogeneity and person-specific effects from mixed models |
| ild_heterogeneity.lme | Heterogeneity and person-specific effects from mixed models |
| ild_heterogeneity.lmerMod | Heterogeneity and person-specific effects from mixed models |
| ild_heterogeneity_stratified | Heterogeneity and person-specific effects from mixed models |
| ild_history | Print a human-readable log of preprocessing or analysis steps |
| ild_ipcw_weights | Inverse probability of censoring weights (IPCW) for monotone dropout |
| ild_iptw_msm_weights | Sequential MSM inverse probability of treatment weights (IPTW for A_t) |
| ild_iptw_weights | Inverse probability of treatment weights (IPTW) |
| ild_ipw_ess | Effective sample size from weights |
| ild_ipw_refit | Refit an ILD model with inverse-probability weights (sensitivity analysis) |
| ild_ipw_weights | Compute inverse-probability-of-observation weights from a missingness model |
| ild_joint_msm_weights | Joint MSM weights from IPTW and IPCW components |
| ild_kfas | Fit a Gaussian state-space model via KFAS (single-subject ILD) |
| ild_lag | Spacing-aware lag within person |
| ild_lme | Fit a linear mixed-effects model to ILD |
| ild_manifest | Create a reproducibility manifest |
| ild_meta | Get ILD metadata attributes |
| ild_methods | Generate methods-style narrative from provenance |
| ild_missingness_report | Missingness workflow report (orchestration) |
| ild_missing_bias | Test whether missingness is associated with a predictor (informative missingness) |
| ild_missing_cohort | Cohort-level fraction observed by occasion index |
| ild_missing_compliance | Person-level missingness compliance for one outcome |
| ild_missing_hazard_first | Discrete hazard of first missing outcome on an ordinal schedule |
| ild_missing_model | Fit a model for missingness (diagnostic / sensitivity) |
| ild_missing_pattern | Summarize missingness pattern in ILD |
| ild_msm_balance | Covariate balance (weighted SMD) for MSM / IPW |
| ild_msm_bootstrap | Cluster bootstrap inference for weighted 'lmer' (MSM / IPW sensitivity) |
| ild_msm_contrast_over_time | Compute MSM contrasts over time from a fitted weighted model |
| ild_msm_diagnose | Diagnose an 'ild_msm_fit' result in one call |
| ild_msm_estimand | Define an MSM estimand specification |
| ild_msm_fit | Fit an MSM-style weighted mixed model from an estimand spec |
| ild_msm_history_spec | Build a declarative MSM history specification |
| ild_msm_overlap_plot | Propensity overlap plot (pooled or sequential MSM IPTW) |
| ild_msm_recovery | MSM recovery simulation harness |
| ild_msm_simulate_scenario | Simulate a simple longitudinal MSM scenario |
| ild_panel_lag_prepare | Prepare several lag columns and audit them |
| ild_person_distribution | Plot distribution of person-level estimates from ild_person_model |
| ild_person_model | Fit a model separately per person (N-of-1 / idiographic) |
| ild_plot | ILD-specific plots |
| ild_plot_filtered_vs_smoothed | Plot filtered vs smoothed state (first state) |
| ild_plot_forecast | Plot forecast or future simulation (stub when no horizon) |
| ild_plot_predicted_trajectory | Observed and fitted values vs time (trajectory overlay) |
| ild_plot_states | Plot smoothed latent states (first state by default) |
| ild_power | Simulation-based power analysis for a fixed effect in ILD models |
| ild_prepare | Prepare a data frame as an ILD (intensive longitudinal data) object |
| ild_prior_ild | Prior specifications for common ILD mixed models |
| ild_provenance | Return the raw provenance object |
| ild_recovery_metrics | Recovery metrics from simulation replications |
| ild_report | Assemble a light report from a model fit |
| ild_robust_se | Cluster-robust variance-covariance matrix for ILD model fits |
| ild_simulate | Simulate simple ILD for examples, tests, and power analysis |
| ild_spacing | Spacing diagnostics and correlation-structure recommendation |
| ild_spacing_class | Classify spacing as regular-ish vs irregular-ish |
| ild_spaghetti | ILD spaghetti / person trajectories (alias for ild_plot with type = "trajectory") |
| ild_summary | One-shot summary of an ILD object |
| ild_tidy | Tidy fixed effects from an ILD model fit (S3 generic) |
| ild_tidy.brmsfit | Tidy fixed effects from an ILD model fit (S3 generic) |
| ild_tidy.default | Tidy fixed effects from an ILD model fit (S3 generic) |
| ild_tidy.ild_fit_ctsem | Tidy fixed effects from an ILD model fit (S3 generic) |
| ild_tidy.ild_fit_kfas | Tidy fixed effects from an ILD model fit (S3 generic) |
| ild_tidy.ild_heterogeneity | Heterogeneity and person-specific effects from mixed models |
| ild_tidy.lme | Tidy fixed effects from an ILD model fit (S3 generic) |
| ild_tidy.lmerMod | Tidy fixed effects from an ILD model fit (S3 generic) |
| ild_tidy_schema | Column dictionary for ild_tidy() outputs |
| ild_tidy_states | Tidy per-time state summaries for ild_kfas |
| ild_tsibble_meta | Tsibble provenance from an ILD object |
| ild_tvem | Fit a time-varying effects model (TVEM) for ILD |
| ild_tvem_plot | Plot the time-varying coefficient from a TVEM fit |
| is_ild | Check if an object is a valid ILD tibble |
| is_ild_diagnostics_bundle | Canonical ILD diagnostics bundle |
-- N --
| new_ild_diagnostics_bundle | Canonical ILD diagnostics bundle |
-- P --
| plot_ild_diagnostics | Plot diagnostics from an ild_diagnostics object |
-- T --
| tidy.ild_lme | Tidy and augment ild_lme fits with broom.mixed |
| tidyILD | tidyILD: Tidy Intensive Longitudinal Data Analysis |
| tidy_ild_model | Tidy fixed effects from an ILD model fit |
| tidy_ild_msm_bootstrap | Tidy fixed effects from 'ild_msm_bootstrap' |
-- V --
| validate_ild | Validate an ILD object and error if invalid |