{
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  "Title": "Two-Phase Genetic Association Study Design and Analysis with\nMissing Covariates by Design",
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  "Authors@R": "c(\nperson(\"Osvaldo\", \"Espin-Garcia\",\nemail = \"oespinga@uwo.ca\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Apostolos\", \"Dimitromanolakis\",\nemail = \"apostolis@live.ca\",\nrole = \"aut\"),\nperson(\"Radu V\", \"Craiu\",\nemail = \"radu.craiu@utoronto.ca\",\nrole = \"ths\"),\nperson(\"Shelley B\", \"Bull\",\nemail = \"bull@lunenfeld.ca\",\nrole = \"ths\"))",
  "Description": "Provides functionality for designing and analysing\ntwo-phase genetic association studies. Phase 1 data usually\ncome from genome-wide association study (GWAS) results and we\nassume phase 2 data will be part of a targeted genome\nsequencing or fine-mapping study. At design stage, the package\nassists in selecting a subset of individuals that will be\nsequenced for phase 2 via alternative approaches, including a\nflexible genetic algorithm (GA) for near-optimal designs. Once\nphase 2 data have been collected, the package implements\nmethods to analyse phase 1 and phase 2 data together using\nsemi-parametric regression models via the\nexpectation-maximization (EM) algorithm. For more details see\nEspin-Garcia, Craiu and Bull (2018) <doi:10.1002/gepi.22099>\nand Espin-Garcia, Craiu and Bull (2021) <doi:10.1002/sim.9211>.",
  "License": "GPL (>= 2)",
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  "Author": "Osvaldo Espin-Garcia [aut, cre], Apostolos Dimitromanolakis\n[aut], Radu V Craiu [ths], Shelley B Bull [ths]",
  "Maintainer": "Osvaldo Espin-Garcia <oespinga@uwo.ca>",
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      "title": "Performs inference on two-phase studies data via semiparametric maximum likelihood.",
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        "1. Simulating two-phase data",
        "2. Selecting a phase 2 subsample",
        "3. Analysis under H₀ (score test)",
        "4. Analysis under Hₐ (Wald test)",
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        "6. Using start.values for warm starts",
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