{
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  "Package": "tidyILD",
  "Title": "Tidy Intensive Longitudinal Data Analysis",
  "Version": "0.4.0",
  "Author": "Alex Litovchenko [aut, cre]",
  "Maintainer": "Alex Litovchenko <al4877@columbia.edu>",
  "Authors@R": "person(given = \"Alex\", family = \"Litovchenko\", role = c(\"aut\", \"cre\"), email = \"al4877@columbia.edu\")",
  "Description": "A reproducible, tidyverse-style framework for intensive\nlongitudinal data analysis in R, with built-in methodological\nsafeguards, provenance tracking, and reporting tools. Encodes\ntime structure, enforces within-between decomposition, provides\nspacing-aware lags, and integrates diagnostics and\nvisualization. Use ild_prepare(), ild_center(), ild_lag(), and\nrelated functions for a unified pipeline from raw EMA/diary\ndata to interpretable models.",
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  "Encoding": "UTF-8",
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  "Date/Publication": "2026-04-18 05:54:09 UTC",
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    "augment_ild_model",
    "augment.ild_lme",
    "guardrail_registry",
    "ild_acf",
    "ild_align",
    "ild_as_tsibble",
    "ild_augment",
    "ild_augment_schema",
    "ild_augment_states",
    "ild_autoplot",
    "ild_brms",
    "ild_brms_dynamics_formula",
    "ild_build_msm_history",
    "ild_bundle",
    "ild_center",
    "ild_center_plot",
    "ild_check_lags",
    "ild_circadian",
    "ild_compare_fits",
    "ild_compare_pipelines",
    "ild_crosslag",
    "ild_ctsem",
    "ild_decomposition",
    "ild_design_check",
    "ild_diagnose",
    "ild_diagnostics",
    "ild_diagnostics_bundle",
    "ild_export_provenance",
    "ild_fit",
    "ild_heatmap",
    "ild_heterogeneity",
    "ild_heterogeneity_stratified",
    "ild_history",
    "ild_ipcw_weights",
    "ild_iptw_msm_weights",
    "ild_iptw_weights",
    "ild_ipw_ess",
    "ild_ipw_refit",
    "ild_ipw_weights",
    "ild_joint_msm_weights",
    "ild_kfas",
    "ild_lag",
    "ild_lme",
    "ild_manifest",
    "ild_meta",
    "ild_methods",
    "ild_missing_bias",
    "ild_missing_cohort",
    "ild_missing_compliance",
    "ild_missing_hazard_first",
    "ild_missing_model",
    "ild_missing_pattern",
    "ild_missingness_report",
    "ild_msm_balance",
    "ild_msm_bootstrap",
    "ild_msm_contrast_over_time",
    "ild_msm_diagnose",
    "ild_msm_estimand",
    "ild_msm_fit",
    "ild_msm_history_spec",
    "ild_msm_overlap_plot",
    "ild_msm_recovery",
    "ild_msm_simulate_scenario",
    "ild_panel_lag_prepare",
    "ild_person_distribution",
    "ild_person_model",
    "ild_plot",
    "ild_plot_filtered_vs_smoothed",
    "ild_plot_forecast",
    "ild_plot_predicted_trajectory",
    "ild_plot_states",
    "ild_power",
    "ild_prepare",
    "ild_prior_ild",
    "ild_provenance",
    "ild_recovery_metrics",
    "ild_report",
    "ild_robust_se",
    "ild_simulate",
    "ild_spacing",
    "ild_spacing_class",
    "ild_spaghetti",
    "ild_summary",
    "ild_tidy",
    "ild_tidy_schema",
    "ild_tidy_states",
    "ild_tsibble_meta",
    "ild_tvem",
    "ild_tvem_plot",
    "is_ild",
    "is_ild_diagnostics_bundle",
    "new_ild_diagnostics_bundle",
    "plot_ild_diagnostics",
    "tidy_ild_model",
    "tidy_ild_msm_bootstrap",
    "tidy.ild_lme",
    "validate_ild"
  ],
  "_datasets": [
    {
      "name": "ema_example",
      "title": "Example EMA-style intensive longitudinal dataset",
      "object": "ema_example",
      "file": "ema_example.rda",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "time",
        "mood",
        "stress"
      ],
      "rows": 140,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "tidyILD-package",
      "title": "tidyILD: Tidy Intensive Longitudinal Data Analysis",
      "topics": [
        "tidyILD-package",
        "tidyILD"
      ]
    },
    {
      "page": "as_ild",
      "title": "Coerce to ILD object",
      "topics": [
        "as_ild"
      ]
    },
    {
      "page": "augment_ild_model",
      "title": "Augment an ILD model fit with fitted values and residuals",
      "topics": [
        "augment_ild_model"
      ]
    },
    {
      "page": "broom_ild_lme",
      "title": "Tidy and augment ild_lme fits with broom.mixed",
      "topics": [
        "augment.ild_lme",
        "broom_ild_lme",
        "tidy.ild_lme"
      ]
    },
    {
      "page": "ema_example",
      "title": "Example EMA-style intensive longitudinal dataset",
      "topics": [
        "ema_example"
      ]
    },
    {
      "page": "guardrail_registry",
      "title": "Guardrail rule registry (analysis safety layer)",
      "topics": [
        "guardrail_registry"
      ]
    },
    {
      "page": "ild_acf",
      "title": "Autocorrelation function for ILD variables or model residuals",
      "topics": [
        "ild_acf"
      ]
    },
    {
      "page": "ild_align",
      "title": "Align a secondary stream to primary ILD within a time window",
      "topics": [
        "ild_align"
      ]
    },
    {
      "page": "ild_as_tsibble",
      "title": "Convert an ILD object to a tsibble",
      "topics": [
        "ild_as_tsibble"
      ]
    },
    {
      "page": "ild_augment",
      "title": "Augment observations with fitted values and residuals (S3 generic)",
      "topics": [
        "ild_augment",
        "ild_augment.brmsfit",
        "ild_augment.default",
        "ild_augment.ild_fit_ctsem",
        "ild_augment.ild_fit_kfas",
        "ild_augment.lme",
        "ild_augment.lmerMod"
      ]
    },
    {
      "page": "ild_augment_schema",
      "title": "Column dictionary for 'ild_augment()' outputs",
      "topics": [
        "ild_augment_schema"
      ]
    },
    {
      "page": "ild_augment_states",
      "title": "Per-row latent states (long format) for complex multi-state models",
      "topics": [
        "ild_augment_states"
      ]
    },
    {
      "page": "ild_autoplot",
      "title": "Autoplot for ILD model fits or diagnostics (S3 generic)",
      "topics": [
        "ild_autoplot",
        "ild_autoplot.brmsfit",
        "ild_autoplot.default",
        "ild_autoplot.ild_diagnostics",
        "ild_autoplot.ild_diagnostics_bundle",
        "ild_autoplot.ild_fit_ctsem",
        "ild_autoplot.ild_fit_kfas",
        "ild_autoplot.lme",
        "ild_autoplot.lmerMod"
      ]
    },
    {
      "page": "ild_brms",
      "title": "Fit a Bayesian mixed model to ILD data with 'brms'",
      "topics": [
        "ild_brms"
      ]
    },
    {
      "page": "ild_brms_dynamics_formula",
      "title": "Template brms formula for person-varying lag slope",
      "topics": [
        "ild_brms_dynamics_formula"
      ]
    },
    {
      "page": "ild_build_msm_history",
      "title": "Build MSM lagged history columns from a spec",
      "topics": [
        "ild_build_msm_history"
      ]
    },
    {
      "page": "ild_bundle",
      "title": "Bundle a result with a reproducibility manifest",
      "topics": [
        "ild_bundle"
      ]
    },
    {
      "page": "ild_center",
      "title": "Within-person and between-person decomposition (centering)",
      "topics": [
        "ild_center"
      ]
    },
    {
      "page": "ild_center_plot",
      "title": "Standalone WP/BP centering plot",
      "topics": [
        "ild_center_plot"
      ]
    },
    {
      "page": "ild_check_lags",
      "title": "Check lag variable validity (gap-aware)",
      "topics": [
        "ild_check_lags"
      ]
    },
    {
      "page": "ild_circadian",
      "title": "Time-of-day pattern plot for ILD (circadian-style)",
      "topics": [
        "ild_circadian"
      ]
    },
    {
      "page": "ild_compare_fits",
      "title": "Compare fitted models (AIC, BIC, nobs)",
      "topics": [
        "ild_compare_fits"
      ]
    },
    {
      "page": "ild_compare_pipelines",
      "title": "Compare provenance of two objects and report differences",
      "topics": [
        "ild_compare_pipelines"
      ]
    },
    {
      "page": "ild_crosslag",
      "title": "Cross-lag model: lag predictor then fit outcome ~ lag",
      "topics": [
        "ild_crosslag"
      ]
    },
    {
      "page": "ild_ctsem",
      "title": "Fit a continuous-time state-space model via ctsem",
      "topics": [
        "ild_ctsem"
      ]
    },
    {
      "page": "ild_decomposition",
      "title": "Within-person and between-person variance decomposition",
      "topics": [
        "ild_decomposition"
      ]
    },
    {
      "page": "ild_design_check",
      "title": "ILD design diagnostics: spacing, WP/BP, missingness, and recommendations",
      "concept": [
        "ild_diagnostics_utilities"
      ],
      "topics": [
        "ild_design_check"
      ]
    },
    {
      "page": "ild_diagnose",
      "title": "Engine-agnostic diagnostics façade",
      "topics": [
        "ild_diagnose",
        "ild_diagnose.brmsfit",
        "ild_diagnose.default",
        "ild_diagnose.ild_fit_ctsem",
        "ild_diagnose.ild_fit_kfas",
        "ild_diagnose.lme",
        "ild_diagnose.lmerMod"
      ]
    },
    {
      "page": "ild_diagnostics",
      "title": "Residual diagnostics for an ILD model",
      "topics": [
        "ild_diagnostics"
      ]
    },
    {
      "page": "ild_diagnostics_bundle",
      "title": "Canonical ILD diagnostics bundle",
      "topics": [
        "ild_diagnostics_bundle",
        "is_ild_diagnostics_bundle",
        "new_ild_diagnostics_bundle"
      ]
    },
    {
      "page": "ild_diagnostics_utilities",
      "title": "Standalone diagnostics utilities and bundle section providers",
      "topics": [
        "ild_diagnostics_utilities"
      ]
    },
    {
      "page": "ild_export_provenance",
      "title": "Export provenance to a JSON or YAML file",
      "topics": [
        "ild_export_provenance"
      ]
    },
    {
      "page": "ild_fit",
      "title": "Fit a mixed model to ILD data (unified entry point)",
      "topics": [
        "ild_fit"
      ]
    },
    {
      "page": "ild_heatmap",
      "title": "ILD heatmap (alias for ild_plot with type = \"heatmap\")",
      "topics": [
        "ild_heatmap"
      ]
    },
    {
      "page": "ild_heterogeneity",
      "title": "Heterogeneity and person-specific effects from mixed models",
      "topics": [
        "ild_autoplot.ild_heterogeneity",
        "ild_heterogeneity",
        "ild_heterogeneity.brmsfit",
        "ild_heterogeneity.lme",
        "ild_heterogeneity.lmerMod",
        "ild_heterogeneity_stratified",
        "ild_tidy.ild_heterogeneity"
      ]
    },
    {
      "page": "ild_history",
      "title": "Print a human-readable log of preprocessing or analysis steps",
      "topics": [
        "ild_history"
      ]
    },
    {
      "page": "ild_ipcw_weights",
      "title": "Inverse probability of censoring weights (IPCW) for monotone dropout",
      "concept": [
        "ild_diagnostics_utilities"
      ],
      "topics": [
        "ild_ipcw_weights"
      ]
    },
    {
      "page": "ild_iptw_msm_weights",
      "title": "Sequential MSM inverse probability of treatment weights (IPTW for A_t)",
      "concept": [
        "ild_diagnostics_utilities"
      ],
      "topics": [
        "ild_iptw_msm_weights"
      ]
    },
    {
      "page": "ild_iptw_weights",
      "title": "Inverse probability of treatment weights (IPTW)",
      "concept": [
        "ild_diagnostics_utilities"
      ],
      "topics": [
        "ild_iptw_weights"
      ]
    },
    {
      "page": "ild_ipw_ess",
      "title": "Effective sample size from weights",
      "topics": [
        "ild_ipw_ess"
      ]
    },
    {
      "page": "ild_ipw_refit",
      "title": "Refit an ILD model with inverse-probability weights (sensitivity analysis)",
      "topics": [
        "ild_ipw_refit"
      ]
    },
    {
      "page": "ild_ipw_weights",
      "title": "Compute inverse-probability-of-observation weights from a missingness model",
      "concept": [
        "ild_diagnostics_utilities"
      ],
      "topics": [
        "ild_ipw_weights"
      ]
    },
    {
      "page": "ild_joint_msm_weights",
      "title": "Joint MSM weights from IPTW and IPCW components",
      "concept": [
        "ild_diagnostics_utilities"
      ],
      "topics": [
        "ild_joint_msm_weights"
      ]
    },
    {
      "page": "ild_kfas",
      "title": "Fit a Gaussian state-space model via KFAS (single-subject ILD)",
      "topics": [
        "ild_kfas"
      ]
    },
    {
      "page": "ild_lag",
      "title": "Spacing-aware lag within person",
      "topics": [
        "ild_lag"
      ]
    },
    {
      "page": "ild_lme",
      "title": "Fit a linear mixed-effects model to ILD",
      "topics": [
        "ild_lme"
      ]
    },
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      "page": "ild_manifest",
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      "page": "ild_meta",
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      "page": "ild_methods",
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      "page": "ild_missing_bias",
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      "topics": [
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      "title": "Compute MSM contrasts over time from a fitted weighted model",
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      "page": "ild_msm_diagnose",
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      "title": "Define an MSM estimand specification",
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      "title": "Fit an MSM-style weighted mixed model from an estimand spec",
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      "page": "ild_msm_overlap_plot",
      "title": "Propensity overlap plot (pooled or sequential MSM IPTW)",
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      "title": "Prior specifications for common ILD mixed models",
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        "Complete-case vs mixed models (careful wording)",
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        "One entry point: ild_missingness_report()",
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      "title": "Reproducible ILD workflows with tidyILD provenance",
      "author": "Alex Litovchenko",
      "engine": "knitr::rmarkdown",
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        "7. Run ild_report()",
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        "9. Compare two pipelines"
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      "title": "Short analysis report",
      "author": "Alex Litovchenko",
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        "AR(1) in the DGP vs residual correlation in the fit",
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      "title": "Specialist backends: when to move beyond the default stack",
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      "title": "State-space modeling in tidyILD with KFAS",
      "author": "Alex Litovchenko",
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        "What is a state-space model?",
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