Package edu.cmu.tetrad.study.missingness

package edu.cmu.tetrad.study.missingness
  • Class
    Description
    BossMissingDataStudy
    Compares the ways Tetrad currently has of running BOSS on data with missing values, on simulated data whose missingness is injected by MissingnessInjector with a chem-shaped rate profile.
    BossMultipleImputationStudy
    Compares BOSS accuracy under the ways Tetrad has of handling missing values, with the two multiple-imputation engines as separate arms: chained equations (MiceLiteImputer) and conditional draws from an EM-fit multivariate normal (MvnImputer).
    DropoutZeroDeletionStudy
    Replication harness for the zero-deletion ("testwise deletion of zeros") proposal of Dai, Ng, Luo, Spirtes, Stojanov and Zhang, "Gene Regulatory Network Inference in the Presence of Dropouts: A Causal View" (ICLR 2024).
    ImputationRegimeStudy
    Does MICE imputation with IMaGES-style pooling generalize beyond the linear Gaussian regime? Two phases, both BOSS at 20% MCAR missingness: MIXED: Lee-Hastie simulation, half the variables discrete, scored by degenerate-Gaussian BIC.
    NabiBoundaryStudy
    Companion study to NabiIdentificationProbe: does the Nabi et al.
    NabiIdentificationProbe
    Numerical probe of the identification boundary in Nabi, Bhattacharya and Shpitser, "Full Law Identification in Graphical Models of Missing Data: Completeness Results" (PMLR 119, 2020).
    PooledDgLrtTest
    Degenerate-Gaussian likelihood-ratio conditional-independence testing under multiple imputation, pooled by the rules for likelihood-ratio statistics: Meng and Rubin (1992) ("D3", the default, which is what the micd package Witte et al.
    PooledDgLrtTest.Pooling
    The pooling rule.
    StroblTestwiseFciStudy
    Replication harness for Strobl, Visweswaran and Spirtes, "Fast Causal Inference with Non-Random Missingness by Test-Wise Deletion" (Int J Data Sci Anal, 2018).
    TestwiseDeletionStudy
    Maps out where test-wise deletion fails and where it is fine, before any decision about its place in the interface.
    WitteReplicationStudy
    Replication harness for Witte, Foraita and Didelez, "Multiple imputation and test-wise deletion for causal discovery with incomplete cohort data" (arXiv:2108.13331, 2021).