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  "Title": "Ensemble Meta-Inference Framework",
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  "Description": "An ensemble meta-inference framework to integrate multiple\nregression models into a current study. Gu, T., Taylor, J.M.G.\nand Mukherjee, B. (2021) <arXiv:2010.09971>. A meta-analysis\nframework along with two weighted estimators as the ensemble of\nempirical Bayes estimators, which combines the estimates from\nthe different external models. The proposed framework is\nflexible and robust in the ways that (i) it is capable of\nincorporating external models that use a slightly different set\nof covariates; (ii) it is able to identify the most relevant\nexternal information and diminish the influence of information\nthat is less compatible with the internal data; and (iii) it\nnicely balances the bias-variance trade-off while preserving\nthe most efficiency gain. The proposed estimators are more\nefficient than the naive analysis of the internal data and\nother naive combinations of external estimators.",
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      "title": "Asymptotic variance-covariance matrix for gamma_Int and gamma_CML for linear regression (continuous outcome Y)",
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    },
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      "title": "Calculate the empirical Bayes (EB) estimates",
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    },
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      ]
    },
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