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  "Package": "magmaanlab",
  "Title": "Methods-development R bindings for the magmaan C++ SEM library",
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  "Description": "Thin Rcpp wrappers exposing magmaan's C++ functions for\nmethods development and research, including frontier methods.\nThe opinionated one-call package for ordinary users is\n'magmaan', which builds on this one. Self-contained: the C++\ncore (plus the vendored PORT and QUADPACK routines) is compiled\nfrom sources vendored under cpp/src/ and linked against a\nsystem NLopt, so the package installs without CMake or a\nprebuilt library. Not CRAN-bound.",
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  "_exports": [
    "association_ml_global_test",
    "association_ml_ij",
    "association_ml_modification_indices",
    "association_ml_nested_test",
    "association_ml_score_tests",
    "augment_model_spec",
    "bounds_loading",
    "bounds_pos_var",
    "bounds_standard",
    "bounds_variance",
    "bounds_wide",
    "calibrate_quadratic",
    "case_rerun",
    "composite_weights",
    "compute_defined",
    "continuous_invariance",
    "convention_fit_measures",
    "convention_inference",
    "convention_nested",
    "convergence_sim",
    "convergence_sim_catalog",
    "convergence_sim_dejonckere_crossloading",
    "convergence_sim_dejonckere_msst",
    "convergence_sim_dejonckere_shrinkage",
    "convergence_sim_dejonckere_simple",
    "convergence_sim_ludtke_cfa",
    "df_to_data",
    "df_to_fcsem_data",
    "df_to_fiml_data",
    "eqs_model",
    "est_change",
    "est_change_approx",
    "est_change_raw",
    "est_change_raw_approx",
    "estimate",
    "factor_score_precision",
    "factor_scores",
    "fcsem_fit_measures",
    "fcsem_model_spec",
    "fcsem_standard_errors",
    "fcsem_standardized_rows",
    "fit_index_intervals_misspec",
    "fit_measures",
    "fit_measures_change",
    "fit_measures_misspec",
    "fit_measures_misspec_mixed_ordinal",
    "fit_measures_noniterative",
    "fit_ml_fcsem",
    "fit_model",
    "fit_noniterative_cfa",
    "fit_noniterative_cfa_metric",
    "fit_noniterative_cfa_restricted",
    "fit_twolevel",
    "fmg_nested",
    "fmg_nested_mixed_ordinal",
    "fmg_nested_ordinal",
    "fmg_pvalues",
    "fmg_tests",
    "fmg_tests_mixed_ordinal",
    "fmg_tests_ordinal",
    "frontier_fit_fiml_multiinfo",
    "frontier_fit_fiml_psd",
    "frontier_fit_gls_psd",
    "frontier_fit_mixed_ordinal_psd",
    "frontier_fit_ml_multiinfo",
    "frontier_fit_ml_psd",
    "frontier_fit_ml_psd_fallback",
    "frontier_fit_ml2s_psd",
    "frontier_fit_ordinal_psd",
    "frontier_fit_sphere",
    "frontier_fit_uls_psd",
    "frontier_fit_wls_psd",
    "frontier_newton_accuracy",
    "frontier_reidentify",
    "global_score_flip_test",
    "guttman_h",
    "inference_covariance",
    "inference_information",
    "inference_quadratic",
    "inference_reuse",
    "inference_rows",
    "lav_residuals",
    "magmaan_core",
    "magmaan_fcsem",
    "mahalanobis_rerun",
    "mi_screen",
    "model_spec",
    "modification_indices",
    "modification_indices_lrt",
    "modification_indices_robust",
    "mplus_data",
    "mplus_model",
    "mplus_wlsmv_invariance",
    "native_pointer_live",
    "nested_score_test",
    "nestedTest",
    "noniterative_cfa_constrained",
    "noniterative_cfa_difference_test",
    "noniterative_cfa_grouped_inference",
    "noniterative_cfa_inference",
    "noniterative_cfa_modification_indices",
    "noniterative_cfa_pseudo_lrt",
    "noniterative_cfa_scalar_invariance",
    "noniterative_cfa_se",
    "noniterative_cfa_wald",
    "parameter_covariance",
    "parameter_table",
    "policy_fit_measures",
    "policy_inference",
    "policy_mi_refit",
    "policy_modification_indices",
    "policy_nested",
    "prepare_data",
    "prepare_hypothesis",
    "prepare_inference",
    "prepare_inference_data",
    "prepare_model",
    "prepare_weight",
    "project_scores",
    "quadratic_reference",
    "refit_from_null",
    "resample_scores",
    "robust_nested_lrt",
    "sam",
    "score_components",
    "score_components_from_matrices",
    "score_flip_test",
    "score_quadratic",
    "score_sandwich",
    "score_spectrum",
    "score_tests",
    "score_tests_lrt",
    "score_tests_robust",
    "scores",
    "sim_model_batch",
    "sim_model_calibrate",
    "sim_model_draw",
    "sim_ordcorr_batch",
    "sim_ordcorr_calibrate",
    "sim_ordcorr_draw",
    "sim_ordcorr_mg_batch",
    "sim_ordcorr_mg_calibrate",
    "sim_ordcorr_mg_draw",
    "sim_ordcorr_mg_summary_calibrate",
    "sim_ordcorr_summary_calibrate",
    "standardized",
    "standardized_rows",
    "structural_identification",
    "version",
    "wald_test"
  ],
  "_help": [
    {
      "page": "association_ml_global_test",
      "title": "Lab association ML global and nested spectral tests",
      "topics": [
        "association_ml_global_test",
        "association_ml_nested_test"
      ]
    },
    {
      "page": "association_ml_ij",
      "title": "Exact sampling sandwich for ordinal association ML",
      "topics": [
        "association_ml_ij"
      ]
    },
    {
      "page": "association_ml_scores",
      "title": "Lab association-ML modification indices and linear releases",
      "topics": [
        "association_ml_modification_indices",
        "association_ml_score_tests"
      ]
    },
    {
      "page": "bounds_loading",
      "title": "Parameter bounds: bounds_loading",
      "topics": [
        "bounds_loading"
      ]
    },
    {
      "page": "bounds_pos_var",
      "title": "Parameter bounds: bounds_pos_var",
      "topics": [
        "bounds_pos_var"
      ]
    },
    {
      "page": "bounds_standard",
      "title": "Parameter bounds: bounds_standard",
      "topics": [
        "bounds_standard"
      ]
    },
    {
      "page": "bounds_variance",
      "title": "Parameter bounds: bounds_variance",
      "topics": [
        "bounds_variance"
      ]
    },
    {
      "page": "bounds_wide",
      "title": "Parameter bounds: bounds_wide",
      "topics": [
        "bounds_wide"
      ]
    },
    {
      "page": "case_rerun",
      "title": "Refit a model repeatedly, each time with one case removed",
      "topics": [
        "case_rerun"
      ]
    },
    {
      "page": "composite_weights",
      "title": "Composite score weights",
      "topics": [
        "composite_weights"
      ]
    },
    {
      "page": "compute_defined",
      "title": "Evaluate defined model parameters",
      "topics": [
        "compute_defined"
      ]
    },
    {
      "page": "continuous_invariance",
      "title": "Fit a continuous-data measurement-invariance ladder.",
      "topics": [
        "continuous_invariance"
      ]
    },
    {
      "page": "convention_fit_measures",
      "title": "Lavaan-compatible fit measures",
      "topics": [
        "convention_fit_measures"
      ]
    },
    {
      "page": "convention_inference",
      "title": "Named lavaan inference on retained estimates",
      "topics": [
        "convention_inference",
        "convention_nested"
      ]
    },
    {
      "page": "convergence_sim",
      "title": "Convergence simulation design: convergence_sim",
      "topics": [
        "convergence_sim"
      ]
    },
    {
      "page": "convergence_sim_catalog",
      "title": "Convergence simulation design: convergence_sim_catalog",
      "topics": [
        "convergence_sim_catalog"
      ]
    },
    {
      "page": "convergence_sim_dejonckere_crossloading",
      "title": "Convergence simulation design: convergence_sim_dejonckere_crossloading",
      "topics": [
        "convergence_sim_dejonckere_crossloading"
      ]
    },
    {
      "page": "convergence_sim_dejonckere_msst",
      "title": "Convergence simulation design: convergence_sim_dejonckere_msst",
      "topics": [
        "convergence_sim_dejonckere_msst"
      ]
    },
    {
      "page": "convergence_sim_dejonckere_shrinkage",
      "title": "Convergence simulation design: convergence_sim_dejonckere_shrinkage",
      "topics": [
        "convergence_sim_dejonckere_shrinkage"
      ]
    },
    {
      "page": "convergence_sim_dejonckere_simple",
      "title": "Convergence simulation design: convergence_sim_dejonckere_simple",
      "topics": [
        "convergence_sim_dejonckere_simple"
      ]
    },
    {
      "page": "convergence_sim_ludtke_cfa",
      "title": "Convergence simulation design: convergence_sim_ludtke_cfa",
      "topics": [
        "convergence_sim_ludtke_cfa"
      ]
    },
    {
      "page": "df_to_data",
      "title": "Prepare data: df_to_data",
      "topics": [
        "df_to_data"
      ]
    },
    {
      "page": "df_to_fcsem_data",
      "title": "Prepare data: df_to_fcsem_data",
      "topics": [
        "df_to_fcsem_data"
      ]
    },
    {
      "page": "df_to_fiml_data",
      "title": "Prepare data: df_to_fiml_data",
      "topics": [
        "df_to_fiml_data"
      ]
    },
    {
      "page": "eqs_model",
      "title": "Construct a model from EQS equations",
      "topics": [
        "eqs_model"
      ]
    },
    {
      "page": "est_change",
      "title": "Summarize case-rerun parameter changes",
      "topics": [
        "est_change"
      ]
    },
    {
      "page": "est_change_approx",
      "title": "Approximate standardized case influence (DFTHETAS) and gCD (one-step)",
      "topics": [
        "est_change_approx"
      ]
    },
    {
      "page": "est_change_raw",
      "title": "Case influence on raw parameter estimates (DFBETA / DFZTHETA)",
      "topics": [
        "est_change_raw"
      ]
    },
    {
      "page": "est_change_raw_approx",
      "title": "Approximate case influence on raw parameter estimates (one-step, no refit)",
      "topics": [
        "est_change_raw_approx"
      ]
    },
    {
      "page": "factor_score_precision",
      "title": "Factor-score precision diagnostics",
      "topics": [
        "factor_score_precision"
      ]
    },
    {
      "page": "factor_scores",
      "title": "Compute factor scores",
      "topics": [
        "factor_scores"
      ]
    },
    {
      "page": "fcsem_fit_measures",
      "title": "Factor-component SEM: fcsem_fit_measures",
      "topics": [
        "fcsem_fit_measures"
      ]
    },
    {
      "page": "fcsem_model_spec",
      "title": "Factor-component SEM: fcsem_model_spec",
      "topics": [
        "fcsem_model_spec"
      ]
    },
    {
      "page": "fcsem_standard_errors",
      "title": "Factor-component SEM: fcsem_standard_errors",
      "topics": [
        "fcsem_standard_errors"
      ]
    },
    {
      "page": "fcsem_standardized_rows",
      "title": "Factor-component SEM: fcsem_standardized_rows",
      "topics": [
        "fcsem_standardized_rows"
      ]
    },
    {
      "page": "fit_index_intervals_misspec",
      "title": "Candidate continuous misspecification-robust fit-index intervals",
      "topics": [
        "fit_index_intervals_misspec"
      ]
    },
    {
      "page": "fit_measures",
      "title": "Normal-theory fit measures, optionally with FMG robust p-values.",
      "topics": [
        "fit_measures"
      ]
    },
    {
      "page": "fit_measures_change",
      "title": "Case influence on fit measures",
      "topics": [
        "fit_measures_change"
      ]
    },
    {
      "page": "fit_measures_misspec",
      "title": "Misspecification-robust ordinal fit measures (estimated-weight intervals)",
      "topics": [
        "fit_measures_misspec"
      ]
    },
    {
      "page": "fit_measures_misspec_mixed_ordinal",
      "title": "Misspecification-robust mixed continuous/ordinal DWLS fit measures",
      "topics": [
        "fit_measures_misspec_mixed_ordinal"
      ]
    },
    {
      "page": "fit_measures_noniterative",
      "title": "Fit indices (CFI/TLI/RMSEA + SRMR) for a non-iterative CFA fit.",
      "topics": [
        "fit_measures_noniterative"
      ]
    },
    {
      "page": "fit_ml_fcsem",
      "title": "Factor-component SEM: fit_ml_fcsem",
      "topics": [
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