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  "Title": "Multiple Imputation Using the General Location Model with the\nEMB Algorithm",
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  "Description": "Provides multiple imputation for mixed continuous and\ncategorical data using the General Location Model (Olkin & Tate\n1961; Little & Schluchter 1987) combined with the\nExpectation-Maximization with Bootstrapping (EMB) algorithm.\nCategorical variables are specified via the noms option; all\nother variables are treated as continuous. The package wraps\nthe EM implementation in the 'mix' package and extends it with\na bootstrap wrapper to produce proper multiple imputations in\nthe sense of Rubin (1987).",
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  "Encoding": "UTF-8",
  "ByteCompile": "true",
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  "Repository": "https://pauldallison.r-universe.dev",
  "Date/Publication": "2026-05-25 21:27:35 UTC",
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    "message": "Fix reproducibility bug with odd number of imputations (v0.1.3)\n\nReplaced mix::imp.mix() with a pure-R imputation function (.glm_impute)\nthat uses R's own seeded RNG. The mix package's Fortran RNG retains\ninternal state across calls and cannot be fully reset by rngseed(),\ncausing glemb() to alternate between two distinct result sets on\nsuccessive calls whenever m is odd.\n\nAlso adds ByteCompile: true to DESCRIPTION for marginal loop speedup.\n\nCo-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>\n",
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      "title": "Multiple Imputation Using the General Location Model with the EMB Algorithm",
      "topics": [
        "glemb"
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        "Running glemb",
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