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  1. 1

    Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial by Smith, Matthew J., Mansournia, Mohammad A., Maringe, Camille, Zivich, Paul N., Cole, Stephen R., Leyrat, Clémence, Belot, Aurélien, Rachet, Bernard, Luque‐Fernandez, Miguel A.

    ISSN: 0277-6715, 1097-0258, 1097-0258
    Published: England Wiley Subscription Services, Inc 30.01.2022
    Published in Statistics in medicine (30.01.2022)
    “…The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize…”
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    Journal Article
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  3. 3

    Nestedness for Dummies (NeD): A user friendly web interface for exploratory nestedness analysis by Strona, Giovanni, Galli, Paolo, Seveso, Davide, Montano, Simone, Fattorini, Simone

    ISSN: 1548-7660, 1548-7660
    Published: Foundation for Open Access Statistics 01.08.2014
    Published in Journal of statistical software (01.08.2014)
    “…Recent theoretical advances in nestedness analysis have led to the introduction of several alternative metrics to overcome most of the problems biasing the use of matrix 'temperature' calculated…”
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    Journal Article
  4. 4

    From code to reliability: Python-powered Paraconsistent Logic for alarm detection in the power gris/ Do codigo a confiabilidade: Logica Paraconsistente impulsionada por Python para a deteccao de alarmes na rede de energia by de Oliveira, Joseffe Barroso, Gino, Joao Vitor Santa Rosa, de Lima, Carlos Jose, Filho, Joao Inacio da Silva

    ISSN: 2178-9010, 2178-9010
    Published: Sindicato das Secretarias e Secretarios do Estado de Sao Paulo 01.10.2023
    Published in GeSec : Revista de Gestão e Secretariado (01.10.2023)
    “… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis…”
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    Journal Article
  5. 5

    Facilitating the Calculation of the Efficient Score Using Symbolic Computing by B. Sibley, Alexander, Li, Zhiguo, Jiang, Yu, Li, Yi-Ju, Chan, Cliburn, Allen, Andrew, Owzar, Kouros

    ISSN: 0003-1305, 1537-2731
    Published: England Taylor & Francis 03.04.2018
    Published in The American statistician (03.04.2018)
    “… In the analysis of data from high-throughput genomic assays, inference on the basis of the score usually enjoys greater stability, considerably higher computational efficiency, and lends itself…”
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    Journal Article
  6. 6

    False Discovery Rate Smoothing by Tansey, Wesley, Koyejo, Oluwasanmi, Poldrack, Russell A., Scott, James G.

    ISSN: 0162-1459, 1537-274X, 1537-274X
    Published: Alexandria Taylor & Francis 03.07.2018
    “…We present false discovery rate (FDR) smoothing, an empirical-Bayes method for exploiting spatial structure in large multiple-testing problems. FDR smoothing…”
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    Journal Article
  7. 7

    Missing Value Imputation in Relational Data Using Variational Inference by Fontaine, Simon, Kang, Jian, Zhu, Ji

    ISSN: 1061-8600, 1537-2715
    Published: United States 11.07.2025
    “…In real-world networks, node attributes are often only partially observed, necessitating imputation to support analysis or enable downstream tasks…”
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    Journal Article
  8. 8

    Black Box Variational Bayesian Model Averaging by Kejzlar, Vojtech, Bhattacharya, Shrijita, Son, Mookyong, Maiti, Tapabrata

    ISSN: 0003-1305, 1537-2731
    Published: Alexandria Taylor & Francis 02.01.2023
    Published in The American statistician (02.01.2023)
    “…For many decades now, Bayesian Model Averaging (BMA) has been a popular framework to systematically account for model uncertainty that arises in situations…”
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    Journal Article
  9. 9

    Unit information prior for adaptive information borrowing from multiple historical datasets by Jin, Huaqing, Yin, Guosheng

    ISSN: 0277-6715, 1097-0258, 1097-0258
    Published: New York Wiley Subscription Services, Inc 10.11.2021
    Published in Statistics in medicine (10.11.2021)
    “… Incorporating historical data in the analysis of the current study is of great importance, as it can help to gain more information, improve efficiency, and provide a more comprehensive evaluation of treatment…”
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    Journal Article